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J-space на микромоделях. Новая интерпретация открытия Anthropic

Недавно Anthropic рассказал об открытии аналога рабочего пространства в LLM — J-space. В предыдущей статье я разобрал почему теория Льва Выготского лучше интерпретирует полученные исследователями результаты.

В этой статье я на основании экспериментов покажу, что аналоги j-space не зависят от размера нейросети, а являются неизбежным этапом эволюции когнитивной структуры, развивающейся под давлением.

TL;DR. Anthropic описывает внутренние «рабочие пространства» модели языком эмерджентности — как свойство, которое появляется у достаточно больших сетей. Я проверил это на микромоделях, где каждую ось представления можно проверить, и сделал три вывода:
Критерию «модель сообщает о правиле...» (verbal report) может удовлетворять представление, которое на самом деле ничего не вычисляет — голова отчёта следует за внесённым правилом на 85–99%, а вычисление за ней не идёт.
Управляющий знак формируется не от факта построения абстракции, а от стоимости её пересчёта. Дешёвое правило сеть не выносит вовне (не заводит управляющего знака), сколько его ни строй.
Управляющие представления возникают не потому, что сеть становится большой, а потому что их становится выгодно хранить. Управляющий знак не возникает. Он окупается.
J-space не эмерджентность, а неизбежная эволюция когнитивной структуры под давлением стоимости — интернализация знака в смысле, близком к Выготскому.

Введение

Исследователи Anthropic вводят набор критериев, по которым внутреннее направление в активациях можно считать «настоящей» репрезентацией концепта, а не корреляционным артефактом. Первый из них — самоотчёт: модель, если её спросить, сообщает, какое правило она применяет. Формулируется это в терминах эмерджентности — структура «возникает» как побочный продукт масштаба и обучения.

В целом, исследователи описывают, а не объясняют. «Возникло» — это не механизм, а констатация факта. Я предлагаю другую гипотезу: когнитивная структура эволюционирует предсказуемо, под конкретным давлением — стоимостью повторного вычисления. Представление становится несущим (психологическим орудием, если угодно по Выготскому), когда хранить его дешевле, чем каждый раз пересчитывать. Это не эмерджентность больших моделей, то же самое делает и маленькая сеть на 4 слоях, если поставить ей задачу, где пересчёт дорог. И именно в этой логике у Выготского знак интернализуется, когда внешнее, дорогое в исполнении действие, сворачивается во внутреннее орудие.

Часть 1

Что было сделано и что получилось

Теория глобального рабочего пространства Баарса, на которую опирается в своей интерпретации Anthropic, описывает сознание как театр: на сцену — в глобальный буфер — выбрасывается победивший исполнительный процесс, и оттуда его содержимое становится доступно всей системе. У Баарса это содержимое каузально нагружено: попало на сцену — значит влияет на поведение. Именно это отождествление — «быть на сцене» и «управлять» — я проверяю.

Эксперимент показывает, что у системы есть две разные вещи, которые GWT сливает в одну: то, что реально несёт вычисление и управляет действием, — и отдельное самоописание, сообщающее, что происходит на сцене, но не обязанное быть причиной. Второе присутствует даже там, где управлять нечем.

Поэтому я развожу их терминологически. Управляющий знак — представление, которое определяется одним свойством: система на него причинно опирается, правка знака меняет вычисление. Самоописание — отдельный слой, который сообщает о правиле, но с вычислением может расходиться. Интересный результат эксперимента в том, что это два разных объекта, а не один, — и что GWT видит только их совпадение, принимая его за правило.

Для того чтобы понять, откуда в сети берётся управляющий знак, я взял крошечную модель, где все её действия относительно прозрачны. Нейросеть решает простую задачу, с одной особенностью: какое именно действие выполнять (сложить, умножить и т.д.), сеть должна решить сама, используя условия задачи. То есть у задачи есть правило выбора действия, и вот это правило мы и ищем: где оно внутри сети и на что влияет.

Дальше я менял два параметра. Первый — насколько дорого это правило вычислять: от «видно сразу из условия» до «надо всерьёз посчитать». Второй — сколько внутренних читателей этим правилом пользуются. И тестировал через прямое вмешательство: если аккуратно подправить представление правила внутри сети, поедет ли за этим сам ответ.

Получилось два результата, которые стоит разнести на два уровня:

Первый уровень — чем сеть считает. Управляющий знак сеть заводит не тогда, когда правило сложное само по себе, а тогда, когда его дорого пересчитывать заново. Дешёвое правило сеть не хранит: она каждый раз подсматривает его из условия задачи. А вот когда пересчёт становится дорогим, ей выгоднее один раз вынести правило «на видное место» внутри себя и раздать всем читателям. Контрольный опыт закрывает лазейку: правило, которое надо строить, но дёшево, управляющего знака так и не получает. Значит дело не в «построении» и не в «сложности» — дело именно в цене повторного вычисления. Это не эмерджентное чудо, а простой экономический расчёт, доступный даже сети из четырёх слоёв.

Второй уровень — как сеть «рассказывает» о своём вычислении. Интересно, что у части сетей есть отдельный внутренний «докладчик», он сообщает, какое правило сейчас применяется. И этот докладчик врёт систематически и уверенно. Если подменить правило, докладчик почти всегда (в 85–99% случаев) бодро отчитывается о новом правиле, а сама сеть продолжает считать по-старому. Отчёт и вычисление разъезжаются. И, ключевое, это происходит даже там, где никакого рабочего пространства нет вообще: докладчику нечего описывать, но он всё равно рапортует. То есть его «отчёт» — не окно в работу сети, а отдельная надпись, живущая своей жизнью.

Два следствия:

Следствие первое: то, что модель говорит о собственном рассуждении, нельзя принимать за доказательство, что она так и рассуждает. Отчёт о вычислении — это не вычисление, а отдельный слой поверх него, и он отделяется от вычисления не по случайности, а по самой своей природе: как только у сети появляется отдельный «рассказчик», он в принципе может говорить одно, а делать другое. Для больших моделей это прямо бьёт по идее «покажи ход рассуждений — и увидишь, как модель думает»: цепочка рассуждений — такой же отдельный рассказчик.

Следствие второе: Управляющий знак не «возникает» — он окупается. Появление внутренней структуры управляется вполне прозрачной силой — ценой пересчёта. То есть дело не в размере сети и не в эмерджентности. У Выготского называется интернализацией знака: дорогое внешнее действие сворачивается во внутреннее орудие, когда пересчитывать каждый раз дороже, чем один раз вынести правило внутрь. С одним уточнением по результатам эксперимента: интернализация порождает не одно орудие, а два разных — то, что реально управляет вычислением, и отдельного «рассказчика», который лишь имитирует управление.

Anthropic выделил пять свойств J-space. Проверяем, что затронул эксперимент:

Устный отчёт. Уточнение. Anthropic говорит об отчёте +каузальности как едином пакете. Но из эксперимента следует, что отчётная компонента отделяется от каузальной.
Направленное рассуждение (внутреннее рассуждение). «Вмешательство в вектор достаточно для изменения вывода». Уточнение - выполняется избирательно.
Гибкая генерализация. «Одно представление — допустимый аргумент для многих последующих функций; перенос в новый контекст обрабатывается корректно». Расхождение: у Anthropic это признаки одного объекта, эксперимент показывает генерализацию как самоотчет и отдельно как причинность.
Избирательность. «Рабочее пространство — малая часть активаций, задействовано не везде, не в рутине вроде парсинга». Подтверждено.
Направленная модуляция. «По команде удерживать концепцию / считать в уме, независимо от выхода; может подтянуть информацию, обычно не в рабочем пространстве». Не рассматривал из-за ограничений микросетей.

Заключение к первой части

Итак, что я могу сказать в итоге. J-space не уникальное свойство огромных нейросетей, его предвестники и аналоги возникают буквально на уровне примитивных нейросетей, развиваясь по мере их усложнения.

То, что нашли исследователи Anthropic не свойство размера, а неизбежная фаза эволюции когнитивной структуры под давлением стоимости: там, где есть цена пересчёта и переиспользование, знак интернализуется — у ребёнка, сворачивающего громкий счёт во внутренний, у мыши, у которой оставили одну вибриссу и заставили закоммититься в одно решение, у сети из четырёх слоёв. А вместе с управляющим знаком тем же шагом рождается и его двойник — самоописание, отделённое от управления.

Самоописание и управление — два разных объекта, а не один: докладчик расходится с вычислением, причём даже там, где управлять нечем. Управляющий знак заводится не от сложности правила, а от цены его пересчёта; дешёвое правило сеть не выносит внутрь. И «доступность многим читателям» (то, что GWT считает признаком рабочего пространства) не совпадает с «несёт вычисление» — они сходятся только под давлением стоимости, а порознь расходятся. Всё это, конечно, про сеть из четырёх слоёв.

Если механизм доменно-независим — а он геометрический, не завязанный на конкретную задачу, — то и на больших моделях отчёт о рассуждении не обязан быть причиной рассуждения. Тогда «покажи ход мыслей» (chain-of-thought) — это тот же отдельный докладчик, и доверять ему как окну внутрь нельзя по его сути. Это гипотеза, проверять на LLM у меня возможности нет.

Что первично, самоописание или управляющий знак, сказать сложно. С одной стороны самоописание не нужно нейросети без приносимой пользы, с другой самоописание есть без управляющего знака. Это основа для следующих экспериментов.

Ниже вторая часть, для тех, кто хочет изучить более подробно, проверить код и логи.

Часть 2.

На чём проводился эксперимент

Четырёхслойный трансформер (d=64, 4 головы) учится на модулярной арифметике по простому p=97. Вход — [a, b, =], ответ — токен (a ∘ b) mod 97, где операция ∘ выбирается правилом от входа. Сеть проходит гроккинг (обобщение после переобучения) и решает задачу на 96–100%.

Правило варьируется контролируемо по двум осям — стоимости и числу потребителей (fan-out: сколько вспомогательных голов читают правило):

A/B — parity(a): правило читается прямо из входа, тривиально. (A — один потребитель, B — четыре.)
C/D — QR(a): правило = квадратичный вычет a, его надо строить и это дорого. (C — один, D — четыре.)
H — ключ: третий токен-ключ k из 8 задаёт операцию через выученную перестановку. Правило надо строить (это не тождество), но дёшево (таблица из 8 строк). Ключевой контроль: изолирует «построение» от «дороговизны».
F — (a+b)%2: вырожденный контроль, где правило = функция самого ответа.
E — (QR(a), QR(b)): 4 класса, обе оси строить. Проверка масштабирования за пределы бинарного правила.

Каждый вариант — 5 сидов.

Метод: три интервенции по позициям + негативный контроль

Правится внутреннее представление правила на конкретных позициях резидуального потока и смотрим, следует ли вычисление:

eq — правим только последний токен =. Проверяется само наличие управляющего знака: несёт ли представление на = вычислительную нагрузку.
src — правим только токен-источник правила (для A это a, для H — ключ). Контроль «редактируем вход».
all — все позиции.

Плюс отдельно голова op— самоотчёт модели «какое правило я сейчас применяю». Расхождение между тем, что говорит op, и тем, что делает main, — это конфабуляция.

Обращу внимание, интервенция на последнем слое (L=3) на токене = — тавтологична, там между правкой и ридаутом нет ни одного слоя. Поэтому несущую метрику мы берём по ранним слоям (0–2), а L=3 держим как негативный контроль. Он вышел ≈ 1% у всех вариантов — то есть хирургическая правка = на слое ридаута не переписывает ответ механически. Значит любой высокий сигнал на ранних слоях — это реальное чтение представления нижележащими слоями, а не артефакт.

Результат 1: отчёт отвязан от вычисления

Существует вмешательство, при котором голова отчёта следует за внесённым правилом почти идеально, а вычисление за ним не идёт. Причём, разрыв не зависит от того, есть ли вообще за представлением управляемое вычисление.

вариант	есть ли управляющий знак (WS_eq)	отчёт следует (existence), %	средний разрыв отчёт−вычисление, %
B	слабый (15)	95.2	84.0
D	есть (59)	59.8	71.2
H	нет (4)	50.8	68.7
F	вырожден (1.5)	98.8	56.2
E	нуль (0.8)	99.6	90.9

(A и C — одноголовые, головы op нет, конфабуляция там не определена по конструкции.)

Смотрите на сцепку. D имеет управляющий знак и конфабулирует. H не имеет его и конфабулирует так же. E не поддаётся управлению вообще, и конфабулирует сильнее всех. Голова отчёта следует за меткой, а не за вычислением, всегда, независимо от того, стоит ли за представлением хоть какая-то несущая структура.

Это прямой контрпример к критерию «verbal report». Самоотчёт проходит представление, которое ничего не решает. Вербальный отчёт — не свидетельство того, что репрезентация несущая; он свидетельствует только о том, что есть считываемая метка. У Выготского это соответствует эгоцентрической речи: сопровождает действие, но не управляет им.

Результат 2: Управляющий знак окупается, а не возникает

Теперь — когда представление действительно несущее. WS_eq: переключается ли вычисление правкой только = (управляющий знак); input: правкой источника; all: правкой всех позиций. Всё в %.

вар	правило	стоимость	потр.	WS_eq	input	all	чтение
A	parity a	дёшево / читается	1	19.7 ± 20.6	2.3	10.0	бимодально
B	parity a	дёшево / читается	4	14.9 ± 11.5	2.9	8.3	broadcast не помог
H	ключ → класс	строить, но ДЁШЕВО	4	4.2 ± 1.9	20.3	70.8	знака НЕТ → маршрутизация
C	QR(a)	строить + ДОРОГО	1	30.1 ± 8.8	6.0	29.0	умеренный, стабильный
D	QR(a)	дорого + broadcast	4	59.2 ± 29.9	42.1	60.0	сильный знак
F	(a+b)%2	вырожден	4	1.5	1.4	1.4	игнорируется
E	QR×QR, 4 класса	оба строить	4	0.8	0.8	0.9	нуль (потолок метода)

Дешёвые правила (A, B, H) управляющего знака не строят. Дорогие (C, D) — строят. Fan-out усиливает эффект только в дорогом случае (D 59 > C 30), а в дешёвом — нет (B 15 ≤ A 20).

Стержень — H. H строит правило (ключ → класс — это выученное непустое отображение, не тождество), но строит дёшево — и управляющего знака не формирует (WS_eq = 4.2%, туго по всем сидам). Зато правка входных позиций переключает его вычисление (all = 70.8%): сеть читает ключ по требованию, не вынося внутрь. Это чистая маршрутизация.

Отсюда точная формулировка оси: несущая переменная — не «надо ли строить абстракцию», а «дорого ли её пересчитывать». Построение само по себе недостаточно. Только дорогое построение (QR требует вычисления квадратичного вычета) выносится в несущее представление на =.

Эталонный случай — D/сид 2: правка = переключает вычисление на 83%, а правка источника — на 3%. Одна сеть, в которой знак управляет, а вход — нет. Это и есть «интернализованный знак»: правило живёт во внутреннем орудии, а не считывается из входа.

Почему это эволюция, а не эмерджентность

Когда говорят об эмерджентности, подразумевают, что структура появляется у достаточно сложных систем как побочный продукт. Данные эксперимента говорят о другом:

Структура появляется у простейшей сети из 4 слоёв — как только пересчёт становится дорогим.
Она не появляется при дешёвом правиле, какой бы «сложной» ни была задача по остальным осям (H строит, E — 4 класса; ни там, ни там несущего знака нет).
Появление управляется одним параметром — стоимостью, — и усиливается вторым (fan-out). Это не возникает, это функция f(стоимость) × f(число потребителей).
Это язык амортизации, а не эмерджентности. И ровно так работает интернализация знака у Выготского: внешнее действие сворачивается во внутреннее орудие тогда, когда его многократное исполнение становится дорогим, а результат — переиспользуемым. Сеть интернализует правило QR в управляющий знак по той же причине, по которой ребёнок сворачивает громкий счёт во внутреннюю операцию: пересчитывать каждый раз дороже, чем хранить.

Отсюда следует, что если сдвигать только стоимость пересчёта, держа всё прочее фиксированным, то и порог формирования управляющего знака будет двигаться монотонно. H с искусственно удорожённым ключевым отображением должен пересечь порог и стать похожим на D. Это тема следующих экспериментов.

Нюансы

A бимодален. «Дешёвое → нет знака держится в среднем, но 2 сида из 5 у A всё-таки строят управляющий знак (WS 52 и 36) без всякой на то нужды. Дешёвая сторона шумная; чистый контроль здесь — H (туго-низкий), а не A. На A как на доказательство «маршрутизации» опираться нельзя.
Конфаунд L8 не воспроизвёлся. У A правка входа переключает вычисление лишь на 2.3%. То есть прежняя история «в A мы правили не пространство, а вход» под позиционно-разрешённой хирургией не подтверждается. Механизм тоньше, чем «читает из входа».
Расхождение. Парный патч и setclass дают разную оценку управляющего знака и в разные стороны по вариантам (у A/B класс выше, у C/D — ниже). Метрика зависит от интервенции..
E — потолок метода, а не отсутствие структуры. На 4 классах ни одна интервенция не переключает вычисление (даже правка всех позиций ≈ 1%). Сдвиг к среднему целевого класса не заставляет MLP пересчитать 4-путёвый выбор операции. E не подтверждает масштабирование управляющего знака — он подтверждает масштабирование конфабуляции (99%) и показывает, что причинная рулёжка упирается в бинарный потолок. Это ограничение инструмента, не вывод о природе E.
Статистика. n=5, разброс на A и D огромный (D std 30). Это распределение, а не среднее; H грокнул 4/5.

Что это меняет для интерпретируемости

Самоотчёт модели о собственном рассуждении нельзя принимать как свидетельство того, что за отчётом стоит несущее вычисление. Голова отчёта в наших сетях уверенно сообщает о правиле, которого не применяет, — в 85–99% случаев, и независимо от того, существует ли вообще управляемое вычисление. Если это переносится на большие модели (а механизм — считываемая метка, диссоциированная от вычислительного пути, — доменно-независим), то «chain-of-thought как окно в рассуждение» опирается на тот самый критерий, который здесь сломан.

А положительная часть: там, где управляющий знак есть, он устроен не как эмерджентная вспышка, а как предсказуемый продукт давления стоимости. Что делает интерпретируемость менее описательной («что там возникло?») и более причинной («при какой стоимости сформируется?»).

Приложение: Код

Код

"""
J-SPACE LEVEL 9c — РЕШАЮЩИЙ ТЕСТ (исправленная версия)
=====================================================
ИСПРАВЛЕНИЯ ОТНОСИТЕЛЬНО L9 (важно для статьи — числа меняются, НЕ переносить старые)
-----------------------------------------------------------------------------------
[FIX-1, блокирующий]  workspace_score раньше брался как max switch% ПО ВСЕМ слоям,
    включая L=N-1. Но интервенция на L=N-1 применяется ПОСЛЕ последнего блока —
    между правкой '=' и ридаутом не остаётся ни одного слоя, только ln_f+head_main
    на позиции '='. patch хирургичен (меняет координату лишь в подпространстве
    {mu_j,mu_i}, сохраняя a,b в ортогональном дополнении), поэтому на L=N-1 ридаут
    почти гарантированно выдаёт op_answer(i,a,b) у ЛЮБОГО загроккавшего варианта.
    Это тавтология — она не отличает A от D.
    Теперь:
        workspace_score = best switch% по слоям 0..N-2  (есть downstream-чтение)
        ws_readout      = switch% на L=N-1              (тавтологический контроль)
    Несущий сигнал живёт на РАННИХ слоях, где правка '=' вынуждает нижележащие
    блоки реально её прочитать, а не переписать заново из a/b.

[FIX-2]  setcoord для режимов 'src'/'all' навязывал позиции-источнику величину
    координаты, посчитанную на '=' (target=ci с последней позиции). Масштабы
    проекций по позициям разные -> цель размерно не та, input_score/all_score
    через setcoord считались мусорно. Теперь target — per-position: ci_pos[s].

[FIX-3]  T3 брал строку с max(op_followed) и на ней мерил разрыв с main — отбор по
    той же величине, которую хотим показать большой. Теперь три числа:
        existence — разрыв на max(op_followed): СУЩЕСТВУЕТ интервенция, где отчёт
                    следует, а вычисление нет (честно как существование);
        at_wsopt  — разрыв на max(switched):    там, где вычислению легче всего
                    последовать — если op всё равно впереди, конфабуляция робастна;
        gap_mean  — средний парный разрыв по всем строкам режима.

[SELF-CONTAINED]  Загрузка весов L8 удалена. Каталог checkpoints_l9c. Первый прогон
    обучает все модели с нуля; далее кэшируются только собственные чекпоинты.
    --retrain принудительно переобучает.

[E-FIX / setclass]  Для многоклассового E (4 класса) парный patch(0,1) тестирует лишь
    ОДНУ под-ось правила и занижает switch (garbage растёт из-за 4 аттракторов). Добавлена
    интервенция setclass: жёстко выставляет классовую идентичность резидуала в целевой
    класс во ВСЁМ между-классовом подпространстве, сохраняя ортогональное дополнение (a,b);
    switched/op усредняются по всем целям. Для бинарных сводится к тому же 1D-направлению,
    что и парный патч -> числа A–H НЕ меняются, setclass идёт сверкой (WSкласс).
    Несущая интервенция выбирается автоматически: setclass для n_ops>2, парная для бинарных.
    E теперь в дефолтном наборе (последним; d=128, 4 класса — МЕДЛЕННО).

ЧТО ПОКАЗАЛ L8 (контекст)
-------------------------
1. ТРИХОТОМИЯ PATCH (грубое вмешательство, все позиции):
       A,B  чётность (читается)      switch  6-8%   garbage 88%   ЛОМАЕТ
       G    a>b (строить, дёшево)    switch  3%     garbage 93%   ЛОМАЕТ
       F    (a+b)%2 (вырожден)       switch  1.5%   garbage 33%   ИГНОРИРУЕТСЯ
       C    QR (строить, дорого)     switch 19%     garbage 73%   частично
       D    QR + 4 потребителя       switch 53%     garbage 43%   ПЕРЕНАПРАВЛЯЕТ
2. КОНФАБУЛЯЦИЯ: голова 'op' СЛЕДУЕТ за патчем в 87-93% даже там, где вычисление
   НЕ следует. Вербальный отчёт диссоциирован от вычисления.
3. Мягкое вмешательство (setcoord) переключает вычисление во ВСЕХ вариантах:
   ось правила каузальна везде — она ХРУПКАЯ в A/B/G и РОБАСТНАЯ в D.

КРИТИЧЕСКИЙ КОНФАУНД (мотивация L9)
----------------------------------
В L8 все вмешательства применялись КО ВСЕМ ПОЗИЦИЯМ, включая токен 'a'. Но в A
правило И ЕСТЬ признак в 'a' — мы редактировали ВХОД, а не рабочее пространство.

РЕШАЮЩИЙ ТЕСТ (T2)
------------------
Вмешательство в три режима:
    'eq'  — только последний токен '='   <- ПРАВИМ РАБОЧЕЕ ПРОСТРАНСТВО
    'src' — только токен-источник правила <- РЕДАКТИРУЕМ ВХОД (контроль)
    'all' — все позиции (как в L8)
    Переключается ли вычисление, когда правится ТОЛЬКО '=' на РАННЕМ слое?
        ДА  -> правило на '=' НЕСУЩЕЕ: настоящее рабочее пространство.
        НЕТ -> сеть читает правило из резидуала источника: маршрутизация.

КОНТРОЛЬ H — «строить, но дёшево»
---------------------------------
H: правило задаётся ТРЕТЬИМ ТОКЕНОМ-КЛЮЧОМ k из K=8 значений (перестановка сидом).
   Не читается из a/b; вычислительно тривиально (таблица 8 строк); но требует
   ПОСТРОЙКИ (k->класс — выученное отображение, не тождество).
       H ≈ D -> достаточно ПОСТРОЙКИ
       H ≈ A -> нужна ДОРОГОВИЗНА пересчёта (амортизация)
   У H четыре позиции [a,b,k,=]; режим 'src' правит токен-ключ (rule_pos=2).

ЗАПУСК
------
    python jspace_level9c.py                 # A,B,C,D,F,H × 5 сидов, с нуля
    python jspace_level9c.py --variants E    # алфавит (медленно)
    python jspace_level9c.py --seeds 7       # больше сидов
    python jspace_level9c.py --retrain       # принудительно переобучить
"""
import os
import json
import time
import argparse
from itertools import permutations
from datetime import datetime
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
try:
    from sklearn.cluster import KMeans
    from sklearn.metrics import silhouette_score
    SKLEARN = True
except ImportError:
    SKLEARN = False
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
P = 97
EQ = 97
PAD = 98
KEY0 = 99                 # токены-ключи: 99..106 (K=8)
K_KEYS = 8
VOCAB_BASE = 99                    # словарь для правил без ключа
VOCAB_KEY = KEY0 + K_KEYS          # 107 — только для варианта H
N_HEADS, N_LAYERS = 4, 4
LAST = N_LAYERS - 1                 # слой ридаута: интервенция на нём тавтологична для 'eq'


def vocab_for(rule):
    """Пер-вариантный словарь: H (правило от токена-ключа) требует 8 доп. токенов."""
    return VOCAB_KEY if rule == "key" else VOCAB_BASE


CKPT_DIR, LOG_DIR = "checkpoints_l9c", "logs_l9c"
TRACK_DIR = "track_l9c"
os.makedirs(CKPT_DIR, exist_ok=True)
os.makedirs(LOG_DIR, exist_ok=True)
os.makedirs(TRACK_DIR, exist_ok=True)
# ---- ОНТОГЕНЕЗ ЗНАКА (T10) ----
TRACK_EVERY = 250          # снимать метрики представления каждые N эпох
POST_GROK_EPOCHS = 20000   # продолжать обучение ПОСЛЕ грокинга (кристаллизация?)
VARIANTS = {
    "A": dict(rule="parity", heads="single", n_ops=2, d=64,
              desc="чётность a — ЧИТАЕТСЯ из входа, 1 потребитель"),
    "B": dict(rule="parity", heads="multi",  n_ops=2, d=64,
              desc="чётность a — ЧИТАЕТСЯ из входа, 4 потребителя"),
    "C": dict(rule="qr",     heads="single", n_ops=2, d=64,
              desc="QR(a) — СТРОИТЬ + ДОРОГО, 1 потребитель"),
    "D": dict(rule="qr",     heads="multi",  n_ops=2, d=64,
              desc="QR(a) — СТРОИТЬ + ДОРОГО, 4 потребителя"),
    "F": dict(rule="sumpar", heads="multi",  n_ops=2, d=64,
              desc="(a+b)%2 — ВЫРОЖДЕННЫЙ (правило = функция ответа)"),
    "H": dict(rule="key",    heads="multi",  n_ops=2, d=64,
              desc="токен-ключ -> правило — СТРОИТЬ, но ДЁШЕВО  <<< КОНТРОЛЬ"),
    "E": dict(rule="qrqr",   heads="multi",  n_ops=4, d=128,
              desc="(QR(a),QR(b)) — 4 класса, оба строить  <<< АЛФАВИТ"),
}
DEFAULT_ORDER = ["A", "B", "C", "D", "F", "H", "E"]  # E последним: 4 класса, d=128, МЕДЛЕННО
HEADS_MULTI = ["main", "parity", "big", "op"]
HEADS_SINGLE = ["main"]
CONTROL = "triv"
QR_SET = {(x * x) % P for x in range(1, P)}
OP_NAMES = ["a+b", "a*b", "a-b", "a+2b"]


def op_answer(k, a, b):
    return [(a + b) % P, (a * b) % P, (a - b) % P, (a + 2 * b) % P][k]


# ==========================================================
# ДАТАСЕТ
# ==========================================================
def make_dataset(rule, seed=0, train_frac=0.8):
    """
    Возвращает (TR, TE, meta). Для rule='key' последовательность [a,b,k,=],
    для остальных [a,b,=]. meta['rule_pos'] — позиция токена-источника правила.
    """
    a, b = torch.meshgrid(torch.arange(P), torch.arange(P), indexing="ij")
    a, b = a.flatten(), b.flatten()
    is_qr = lambda t: torch.tensor([0 if int(x) in QR_SET else 1 for x in t]).long()
    key = None
    if rule == "parity":
        cls = (a % 2).long(); rule_pos = 0
    elif rule == "qr":
        cls = is_qr(a); rule_pos = 0
    elif rule == "sumpar":
        cls = ((a + b) % 2).long(); rule_pos = 0
    elif rule == "qrqr":
        cls = (is_qr(a) * 2 + is_qr(b)).long(); rule_pos = 0
    elif rule == "key":
        # ключ k из 8; отображение k -> класс фиксировано сидом (не тождество)
        g = torch.Generator().manual_seed(1000 + seed)
        key = torch.randint(0, K_KEYS, (a.numel(),), generator=g)
        perm = torch.randperm(K_KEYS, generator=g)
        key2cls = torch.zeros(K_KEYS, dtype=torch.long)
        key2cls[perm[:K_KEYS // 2]] = 0
        key2cls[perm[K_KEYS // 2:]] = 1
        cls = key2cls[key]
        rule_pos = 2                      # токен ключа
    else:
        raise ValueError(rule)
    n_ops = 4 if rule == "qrqr" else 2
    y_main = torch.zeros_like(a)
    for k in range(n_ops):
        y_main = torch.where(cls == k, op_answer(k, a, b), y_main)
    if rule == "key":
        X = torch.stack([a, b, KEY0 + key, torch.full_like(a, EQ)], dim=1)
    else:
        X = torch.stack([a, b, torch.full_like(a, EQ)], dim=1)
    data = dict(X=X, main=y_main, cls=cls, a=a, b=b,
                parity=(y_main % 2 == 0).long(),
                big=(y_main > P // 2).long(),
                op=cls,
                triv=(b % 2 == 0).long())
    g = torch.Generator().manual_seed(seed)
    idx = torch.randperm(X.size(0), generator=g)
    split = int(len(idx) * train_frac)
    pack = lambda ii: {k: v[ii].to(device) for k, v in data.items()}
    # насколько правило читается из токена a (доля a с однозначным классом)
    pure_a = float(np.mean([len(set(cls[a == v].tolist())) == 1 for v in range(P)]))
    meta = dict(rule=rule, n_ops=n_ops, seq_len=X.size(1), rule_pos=rule_pos,
                readable_from_a=round(pure_a, 3),
                class_balance=[round(float((cls == k).float().mean()), 3) for k in range(n_ops)])
    if rule == "key":
        meta["key2cls"] = key2cls.tolist()
    return pack(idx[:split]), pack(idx[split:]), meta


# ==========================================================
# МОДЕЛЬ
# ==========================================================
class Block(nn.Module):
    def __init__(self, d, h):
        super().__init__()
        self.ln1, self.ln2 = nn.LayerNorm(d), nn.LayerNorm(d)
        self.attn = nn.MultiheadAttention(d, h, batch_first=True)
        self.mlp = nn.Sequential(nn.Linear(d, 4 * d), nn.GELU(), nn.Linear(4 * d, d))

    def forward(self, x):
        n = self.ln1(x)
        o, _ = self.attn(n, n, n)
        x = x + o
        return x + self.mlp(self.ln2(x)), o, None


class Net(nn.Module):
    def __init__(self, heads_mode, n_ops, d, seq_len, vocab=VOCAB_BASE):
        super().__init__()
        self.heads_mode, self.n_ops, self.d, self.vocab = heads_mode, n_ops, d, vocab
        self.embed = nn.Embedding(vocab, d)
        self.pos = nn.Parameter(torch.randn(1, seq_len, d) * 0.02)
        self.layers = nn.ModuleList([Block(d, N_HEADS) for _ in range(N_LAYERS)])
        self.ln_f = nn.LayerNorm(d)
        self.head_main = nn.Linear(d, vocab)
        self.head_triv = nn.Linear(d, 2)
        if heads_mode == "multi":
            self.head_parity = nn.Linear(d, 2)
            self.head_big = nn.Linear(d, 2)
            self.head_op = nn.Linear(d, n_ops)

    def active_heads(self):
        return HEADS_MULTI if self.heads_mode == "multi" else HEADS_SINGLE

    def forward(self, x, intervention=None, cache=False):
        res = self.embed(x) + self.pos[:, :x.size(1), :]
        C = {"res": [res.clone()]} if cache else None
        for i, layer in enumerate(self.layers):
            res, _, _ = layer(res)
            if intervention is not None and intervention["layer"] == i:
                res = intervene(res, intervention)
            if cache:
                C["res"].append(res.clone())
        h = self.ln_f(res[:, -1, :])
        out = {"main": self.head_main(h), "triv": self.head_triv(h)}
        if self.heads_mode == "multi":
            out["parity"] = self.head_parity(h)
            out["big"] = self.head_big(h)
            out["op"] = self.head_op(h)
        return (out, C) if cache else out


def positions_for(mode, seq_len, rule_pos):
    """Какие позиции правим: 'eq' — только последняя, 'src' — токен-источник, 'all' — все."""
    if mode == "eq":
        return [seq_len - 1]
    if mode == "src":
        return [rule_pos]
    return list(range(seq_len))


def intervene(res, iv):
    """
    patch    — обмен координат в базисе {v_src, v_tgt} на ЗАДАННЫХ позициях
    setcoord — вырезать проекцию на ось и подставить target на ЗАДАННЫХ позициях
               (target может быть скаляром ИЛИ тензором [S] — per-position)  [FIX-2]
    ablate   — занулить проекцию
    add      — грубое прибавление (случайный контроль)
    """
    res = res.clone()
    t = iv["type"]
    pos = iv.get("positions", list(range(res.size(1))))
    if t == "patch":
        vs, vt, al = iv["v_src"], iv["v_tgt"], iv.get("alpha", 1.0)
        for s in pos:
            V = torch.stack([vs[s], vt[s]], dim=1)
            c = res[:, s, :] @ torch.linalg.pinv(V).T
            res[:, s, :] = res[:, s, :] + al * ((c.flip(-1) - c) @ V.T)
        return res
    if t == "setcoord":
        u, tgt = iv["axis"], iv["target"]
        for s in pos:
            ts = tgt[s] if torch.is_tensor(tgt) else tgt   # [FIX-2] per-position target
            cur = res[:, s, :] @ u[s]
            res[:, s, :] = res[:, s, :] + (ts - cur).unsqueeze(-1) * u[s].unsqueeze(0)
        return res
    if t == "setclass":
        # [E-FIX] жёстко выставить КЛАССОВУЮ идентичность в целевой класс i во ВСЁМ
        # между-классовом подпространстве, сохранив ортогональное дополнение (там a,b).
        # Обобщение парного патча на n классов. Для n_ops=2 сводится к 1D-оси.
        cmeans, g, basis, i = iv["cmeans"], iv["grand"], iv["basis"], iv["target"]
        for s in pos:
            Q = basis[s]                                   # [d, r] ортонормир. столбцы
            x = res[:, s, :] - g[s]                         # центрируем
            x_between = (x @ Q) @ Q.T                       # проекция на между-классовое
            x_within = x - x_between                        # ортог. дополнение (a,b)
            tgt_between = cmeans[i][s] - g[s]               # идентичность класса i
            res[:, s, :] = g[s] + x_within + tgt_between
        return res
    if t == "ablate":
        v = iv["vec"]
        for s in pos:
            vs_ = v[s]
            pr = (res[:, s, :] @ vs_) / ((vs_ * vs_).sum() + 1e-8)
            res[:, s, :] = res[:, s, :] - pr.unsqueeze(-1) * vs_.unsqueeze(0)
        return res
    if t == "add":
        v, al = iv["vec"], iv.get("alpha", 1.0)
        for s in pos:
            vn = v[s] / (v[s].norm() + 1e-8)
            sc = res[:, s, :].norm(dim=-1, keepdim=True).mean()
            res[:, s, :] = res[:, s, :] + al * vn.unsqueeze(0) * sc
        return res
    raise ValueError(t)


# ==========================================================
# T10. ОНТОГЕНЕЗ ЗНАКА — когда рождается ось правила?
# ==========================================================
def track_snapshot(model, TR, TE, n_ops, meta, pair=(0, 1)):
    """
    Быстрый срез представления. ws_switch здесь считается по РАННИМ слоям (0..N-2),
    как и headline-метрика в T2 [FIX-1] — трекинг тавтологического L=N-1 бессмыслен.
    """
    i, j = pair
    model.eval()
    S, rp = meta["seq_len"], meta["rule_pos"]
    with torch.no_grad():
        acc = float((model(TE["X"])["main"].argmax(1) == TE["main"]).float().mean())
    with torch.no_grad():
        _, Ctr = model(TR["X"], cache=True)
    emb = Ctr["res"][0]
    e_i = emb[TR["cls"] == i].mean(0)[rp]
    e_j = emb[TR["cls"] == j].mean(0)[rp]
    u_emb = (e_i - e_j)
    u_emb = u_emb / (u_emb.norm() + 1e-8)
    m = TE["cls"] == j
    X, a_, b_ = TE["X"][m], TE["a"][m], TE["b"][m]
    ans_tgt = op_answer(i, a_, b_)
    pos_eq = [S - 1]
    best = dict(ws_switch=0.0, layer=-1, axis_norm=0.0, cos_to_input=0.0, silhouette=0.0)
    for L in range(LAST):                         # [FIX-1] только 0..N-2
        r = Ctr["res"][L + 1]
        mu_i = r[TR["cls"] == i].mean(0)
        mu_j = r[TR["cls"] == j].mean(0)
        delta = mu_i - mu_j                                # [S, d]
        with torch.no_grad():
            o = model(X, intervention=dict(layer=L, type="patch", positions=pos_eq,
                                           v_src=mu_j, v_tgt=mu_i, alpha=1.0))
            sw = float((o["main"].argmax(1) == ans_tgt).float().mean()) * 100
        if sw > best["ws_switch"]:
            d_eq = delta[-1]                               # ось правила на токене '='
            cos = float(torch.abs(torch.dot(d_eq / (d_eq.norm() + 1e-8), u_emb)))
            sil = 0.0
            if SKLEARN:
                with torch.no_grad():
                    _, Cte = model(TE["X"], cache=True)
                v = Cte["res"][L + 1][:, -1, :].cpu().numpy()
                try:
                    km = KMeans(n_ops, random_state=0, n_init=5).fit_predict(v)
                    sil = float(silhouette_score(v, km))
                except Exception:
                    sil = 0.0
            best = dict(ws_switch=round(sw, 2), layer=L,
                        axis_norm=round(float(d_eq.norm()), 4),
                        cos_to_input=round(cos, 4), silhouette=round(sil, 4))
    return dict(acc=round(acc, 4), **best)


# ==========================================================
# ОБУЧЕНИЕ
# ==========================================================
def accs(out, D, keys):
    return {k: (out[k].argmax(1) == D[k]).float().mean().item() for k in keys if k in out}


def train_variant(vid, seed, retrain, target=0.95, track=False):
    """
    track=True -> каждые TRACK_EVERY эпох снимается срез представления (T10),
    и обучение продолжается ещё POST_GROK_EPOCHS эпох после грокинга.
    SELF-CONTAINED: загрузка весов L8 удалена; используются только собственные
    чекпоинты L9c. Первый прогон обучает с нуля.
    """
    cfg = VARIANTS[vid]
    max_epochs = 60000 if cfg["n_ops"] == 4 else 40000
    TR, TE, meta = make_dataset(cfg["rule"], seed=seed)
    torch.manual_seed(seed)
    vocab = vocab_for(cfg["rule"])
    model = Net(cfg["heads"], cfg["n_ops"], cfg["d"], meta["seq_len"], vocab).to(device)
    tag = f"{vid}_s{seed}" + ("_trk" if track else "")
    ckpt = os.path.join(CKPT_DIR, tag + ".pth")
    trk_path = os.path.join(TRACK_DIR, f"{vid}_s{seed}.json")
    # ПЕРЕИСПОЛЬЗОВАНИЕ ТОЛЬКО СОБСТВЕННЫХ ВЕСОВ L9c (никаких L8).
    # При --track переобучение обязательно: нужна траектория по ходу обучения.
    if not retrain and not track and os.path.exists(ckpt):
        try:
            sd = torch.load(ckpt, map_location=device, weights_only=True)
            model.load_state_dict(sd)
            print(f"[+] {tag}: веса из собственного чекпоинта L9c ({ckpt})")
            with torch.no_grad():
                g = float((model(TE["X"])["main"].argmax(1) == TE["main"]).float().mean()) >= target
            tl = dict(loaded=True, source="L9c", grokked=bool(g))
            if not tl["grokked"]:
                print(f"  [!] загруженная модель НЕ ЗАГРОККАЛА — из агрегата исключается")
            return model, TR, TE, meta, tl
        except Exception as ex:
            print(f"[!] чекпоинт {ckpt} не подошёл ({type(ex).__name__}) — обучаю с нуля")
    print(f"\n[*] {tag}: {cfg['desc']}")
    print(f"    правило читается из a: {meta['readable_from_a']*100:.0f}% | "
          f"позиция источника: {meta['rule_pos']} | seq_len {meta['seq_len']}")
    if track:
        print(f"    [T10] трекинг каждые {TRACK_EVERY} эпох; после грокинга "
              f"ещё {POST_GROK_EPOCHS} эпох (кристаллизация)")
    opt = torch.optim.AdamW(model.parameters(), lr=1e-3, weight_decay=1.0, betas=(0.9, 0.98))
    keys = model.active_heads() + [CONTROL]
    curve, trace, t0, grok = [], [], time.time(), None
    stop_at = max_epochs
    for e in range(max_epochs):
        model.train(); opt.zero_grad()
        out = model(TR["X"])
        loss = sum(F.cross_entropy(out[k], TR[k]) for k in keys)
        loss.backward(); opt.step()
        if track and e % TRACK_EVERY == 0:
            snap = track_snapshot(model, TR, TE, cfg["n_ops"], meta)
            snap["epoch"] = e
            snap["grokked"] = grok is not None
            trace.append(snap)
            if e % (TRACK_EVERY * 4) == 0:
                print(f"  [T10] E{e:6d} acc {snap['acc']:.3f} | ws_switch {snap['ws_switch']:5.1f}% "
                      f"| |ось| {snap['axis_norm']:.3f} | cos→вход {snap['cos_to_input']:.3f} "
                      f"| sil {snap['silhouette']:.3f} | L{snap['layer']}")
        if e % 500 == 0:
            model.eval()
            with torch.no_grad():
                a_te = accs(model(TE["X"]), TE, keys)
            curve.append(dict(epoch=e, loss=round(loss.item(), 4),
                              test={k: round(v, 4) for k, v in a_te.items()}))
            if not track or e % 2000 == 0:
                print(f"  E{e:6d} loss {loss.item():6.3f} | " +
                      " ".join(f"{k} {v:.3f}" for k, v in a_te.items()))
            if grok is None and a_te["main"] >= target:
                grok = e
                print(f"  [!] ГРОККИНГ @ {e} ({time.time()-t0:.0f}s)")
                if not track:
                    break
                stop_at = min(max_epochs, e + POST_GROK_EPOCHS)
                print(f"  [T10] продолжаю до {stop_at} — смотрим, дозревает ли ось")
            model.train()
        if e >= stop_at:
            print(f"  [T10] пост-грокинг завершён на {e}")
            break
    if grok is None:
        print(f"  [!!!] НЕ ЗАГРОККАЛ — результаты аудита НЕВАЛИДНЫ, из агрегата исключён")
    torch.save(model.state_dict(), ckpt)
    tl = dict(epochs_to_grok=grok, grokked=grok is not None,
              wall_sec=round(time.time() - t0, 1), curve=curve)
    if track and trace:
        tl["track"] = trace
        with open(trk_path, "w", encoding="utf-8") as f:
            json.dump(dict(variant=vid, seed=seed, grok=grok, trace=trace),
                      f, ensure_ascii=False, indent=2)
        analyze_ontogeny(trace, grok, vid, seed)
    return model, TR, TE, meta, tl


def analyze_ontogeny(trace, grok, vid, seed):
    """Разбор кривой онтогенеза: КОГДА рождается ось относительно грокинга?"""
    if not trace or grok is None:
        return None
    ws = np.array([t["ws_switch"] for t in trace])
    ep = np.array([t["epoch"] for t in trace])
    acc = np.array([t["acc"] for t in trace])
    cos = np.array([t["cos_to_input"] for t in trace])
    peak = float(ws.max())
    if peak < 5:
        verdict = "оси нет ни на одном этапе"
        e_axis = None
    else:
        half = peak / 2
        idx = int(np.argmax(ws >= half))
        e_axis = int(ep[idx])
        d = e_axis - grok
        if d < -500:
            verdict = f"ось ДО грокинга (на {-d} эпох раньше) -> знак = ПРЕДПОСЫЛКА"
        elif d > 500:
            verdict = f"ось ПОСЛЕ грокинга (на {d} эпох позже) -> КРИСТАЛЛИЗАЦИЯ"
        else:
            verdict = "ось ВМЕСТЕ с грокингом -> представление = обобщение"
    ws_at_grok = float(ws[np.argmin(np.abs(ep - grok))])
    ws_final = float(ws[-1])
    growth = ws_final - ws_at_grok
    print(f"\n  [T10] ОНТОГЕНЕЗ ЗНАКА ({vid}/s{seed}):")
    print(f"        грокинг @ {grok} | ось (полумакс) @ {e_axis} | ВЕРДИКТ: {verdict}")
    print(f"        ws_switch: в момент грокинга {ws_at_grok:.1f}% -> в конце {ws_final:.1f}% "
          f"(рост {growth:+.1f} п.п.)")
    print(f"        cos→вход:  в момент грокинга "
          f"{float(cos[np.argmin(np.abs(ep - grok))]):.3f} -> в конце {float(cos[-1]):.3f}")
    if growth > 10:
        print(f"        >>> КРИСТАЛЛИЗАЦИЯ ПОДТВЕРЖДЕНА: ось дозревает при неизменной точности "
              f"(acc {float(acc[np.argmin(np.abs(ep-grok))]):.3f} -> {float(acc[-1]):.3f})")
    return dict(grok=grok, axis_epoch=e_axis, verdict=verdict,
                ws_at_grok=round(ws_at_grok, 2), ws_final=round(ws_final, 2),
                growth=round(growth, 2),
                cos_at_grok=round(float(cos[np.argmin(np.abs(ep - grok))]), 4),
                cos_final=round(float(cos[-1]), 4))


# ==========================================================
# ИНСТРУМЕНТЫ
# ==========================================================
def class_means(model, X, cls, L, n_ops):
    model.eval()
    with torch.no_grad():
        _, C = model(X, cache=True)
    r = C["res"][L + 1]
    return [r[cls == k].mean(0) for k in range(n_ops)]


def pair_axis(mu, i, j):
    d = mu[i] - mu[j]
    return d / (d.norm(dim=-1, keepdim=True) + 1e-8)


def class_subspace(mu):
    """
    Для setclass: из классовых средних mu (list из [S,d]) строим
      cmeans [n_ops,S,d], grand [S,d], basis — список по позициям ортонормированных
      базисов Q_s [d,r] между-классового подпространства (r = ранг центрированных средних,
      обычно n_ops-1). Для n_ops=2 r=1 -> одно дискриминантное направление, и setclass
      совпадает с парным патчем по механике.
    """
    M = torch.stack(mu)                    # [n_ops, S, d]
    g = M.mean(0)                          # [S, d]
    Mc = M - g                             # [n_ops, S, d]
    S = M.size(1)
    r_cap = max(1, M.size(0) - 1)          # центрир. средние: ранг <= n_ops-1
    basis = []
    for s in range(S):
        A = Mc[:, s, :]                    # [n_ops, d]
        _, Sg, Vh = torch.linalg.svd(A, full_matrices=False)
        thr = 1e-5 * float(Sg[0]) if Sg.numel() and float(Sg[0]) > 0 else 1e-8
        r = min(r_cap, max(1, int((Sg > thr).sum())))
        basis.append(Vh[:r].T.contiguous())   # [d, r]
    return M, g, basis


# ==========================================================
# T0. ПОТОКИ
# ==========================================================
def T0_flows(model, TE, n_ops, meta):
    model.eval()
    with torch.no_grad():
        _, C = model(TE["X"], cache=True)
    c, S = TE["cls"], TE["X"].size(1)

    def spread(t):
        ms = torch.stack([t[c == k].mean(0) for k in range(n_ops)])
        g = ms.mean(0)
        return [round(float(torch.stack([torch.norm(ms[k, s] - g[s])
                                         for k in range(n_ops)]).mean()), 4) for s in range(S)]
    out = dict(embedding=spread(C["res"][0]),
               residuals=[dict(layer=i, spread=spread(C["res"][i + 1])) for i in range(N_LAYERS)])
    rp = meta["rule_pos"]
    eq = [r["spread"][-1] for r in out["residuals"]]
    src = [r["spread"][rp] for r in out["residuals"]]
    out["summary"] = dict(emb_at_src=out["embedding"][rp], emb_at_eq=out["embedding"][-1],
                          peak_at_eq=round(max(eq), 4), peak_layer=int(np.argmax(eq)),
                          eq_traj=eq, src_traj=src)
    print(f"  T0: эмб@источник {out['summary']['emb_at_src']:.4f} | "
          f"пик@'=' {out['summary']['peak_at_eq']:.4f} (L{out['summary']['peak_layer']})")
    print(f"      траектория '=': {eq}")
    print(f"      траектория источника: {src}")
    return out


# ==========================================================
# T2. РЕШАЮЩИЙ ТЕСТ — ВМЕШАТЕЛЬСТВО ПО ПОЗИЦИЯМ
# ==========================================================
def T2_positions(model, TR, TE, n_ops, meta, pair=(0, 1)):
    """
    Три режима вмешательства:
        'eq'  — только последний токен '='  -> ПРАВИМ РАБОЧЕЕ ПРОСТРАНСТВО
        'src' — только токен-источник       -> РЕДАКТИРУЕМ ВХОД (контроль)
        'all' — все позиции                 -> как в L8
    Для каждого: patch (грубо) и setcoord (мягко, per-position target [FIX-2]).

    [FIX-1] headline workspace_score берётся по РАННИМ слоям 0..N-2; интервенция
    на L=N-1 (позиция ридаута, слой ридаута) тавтологична и логируется отдельно
    как ws_readout.
    """
    i, j = pair
    m = TE["cls"] == j
    X, a_, b_ = TE["X"][m], TE["a"][m], TE["b"][m]
    ans_src, ans_tgt = op_answer(j, a_, b_), op_answer(i, a_, b_)
    S, rp = meta["seq_len"], meta["rule_pos"]
    multi = model.heads_mode == "multi"
    tgt_op = torch.full_like(TE["op"][m], i)
    print("  T2: РЕШАЮЩИЙ ТЕСТ — вмешательство по позициям")
    print(f"      {'режим':<5} {'L':<2} {'α':>4} | {'orig%':>7} {'SWITCH%':>8} {'garb%':>7} | "
          f"{'op→%':>6}")
    rows = []
    for mode in ["eq", "src", "all"]:
        pos = positions_for(mode, S, rp)
        for L in range(N_LAYERS):
            mu = class_means(model, TR["X"], TR["cls"], L, n_ops)
            u = pair_axis(mu, i, j)                 # [S, d]
            ci_pos = (mu[i] * u).sum(-1)            # [FIX-2] per-position target [S]
            for al in [0.5, 1.0, 2.0]:
                with torch.no_grad():
                    o = model(X, intervention=dict(layer=L, type="patch", positions=pos,
                                                   v_src=mu[j], v_tgt=mu[i], alpha=al))
                    pr = o["main"].argmax(1)
                    so = float((pr == ans_src).float().mean()) * 100
                    sp = float((pr == ans_tgt).float().mean()) * 100
                    r = dict(mode=mode, kind="patch", layer=L, alpha=al,
                             orig=round(so, 2), switched=round(sp, 2),
                             garbage=round(100 - so - sp, 2))
                    if multi:
                        r["op_followed"] = round(
                            float((o["op"].argmax(1) == tgt_op).float().mean()) * 100, 2)
                    rows.append(r)
            # мягкое: выставить координату в значение целевого класса ПО КАЖДОЙ позиции
            with torch.no_grad():
                o = model(X, intervention=dict(layer=L, type="setcoord", positions=pos,
                                               axis=u, target=ci_pos))
                pr = o["main"].argmax(1)
                so = float((pr == ans_src).float().mean()) * 100
                sp = float((pr == ans_tgt).float().mean()) * 100
                r = dict(mode=mode, kind="setcoord", layer=L, alpha=None,
                         orig=round(so, 2), switched=round(sp, 2),
                         garbage=round(100 - so - sp, 2))
                if multi:
                    r["op_followed"] = round(
                        float((o["op"].argmax(1) == tgt_op).float().mean()) * 100, 2)
                rows.append(r)

    # ---- setclass: КОРРЕКТНАЯ многоклассовая интервенция (обязательна для E) ----
    # Жёстко выставляем классовую идентичность в целевой класс i во всём между-классовом
    # подпространстве. switched/orig/op усредняются по ВСЕМ целям i (для бинарных это i∈{0,1},
    # для E — i∈{0,1,2,3}). Для бинарных совпадает по механике с парным патчем -> сверка.
    Xall, clsall, mainall = TE["X"], TE["cls"], TE["main"]
    aall, ball = TE["a"], TE["b"]
    for mode in ["eq", "src", "all"]:
        pos = positions_for(mode, S, rp)
        for L in range(N_LAYERS):
            mu = class_means(model, TR["X"], TR["cls"], L, n_ops)
            M, gmean, basis = class_subspace(mu)
            sw_t, or_t, op_t = [], [], []
            for it in range(n_ops):
                msk = clsall != it
                Xi = Xall[msk]
                ans_i = op_answer(it, aall[msk], ball[msk])
                with torch.no_grad():
                    o = model(Xi, intervention=dict(layer=L, type="setclass", positions=pos,
                                                    cmeans=M, grand=gmean, basis=basis, target=it))
                    pr = o["main"].argmax(1)
                sw_t.append(float((pr == ans_i).float().mean()) * 100)
                or_t.append(float((pr == mainall[msk]).float().mean()) * 100)
                if multi:
                    op_t.append(float((o["op"].argmax(1) == it).float().mean()) * 100)
            sw, orr = float(np.mean(sw_t)), float(np.mean(or_t))
            r = dict(mode=mode, kind="setclass", layer=L, alpha=None,
                     orig=round(orr, 2), switched=round(sw, 2),
                     garbage=round(100 - orr - sw, 2),
                     per_target_switch=[round(x, 2) for x in sw_t])
            if multi:
                r["op_followed"] = round(float(np.mean(op_t)), 2)
            rows.append(r)

    PAIR_KINDS = ("patch", "setcoord")

    def _best(mode, kinds, early=False):
        sub = [r for r in rows if r["mode"] == mode and r["kind"] in kinds]
        if early:                                   # [FIX-1] исключить тавтологический L=N-1
            sub2 = [r for r in sub if r["layer"] < LAST]
            sub = sub2 if sub2 else sub
        return max(sub, key=lambda r: r["switched"]) if sub else None

    best_pair       = {m: _best(m, PAIR_KINDS)             for m in ["eq", "src", "all"]}
    best_pair_early = {m: _best(m, PAIR_KINDS, early=True) for m in ["eq", "src", "all"]}
    best_cls        = {m: _best(m, ("setclass",))             for m in ["eq", "src", "all"]}
    best_cls_early  = {m: _best(m, ("setclass",), early=True) for m in ["eq", "src", "all"]}

    # авто: несущая интервенция — КЛАССОВАЯ для многоклассовых (E), ПАРНАЯ для бинарных
    use_class = n_ops > 2
    head_early = best_cls_early if use_class else best_pair_early
    head_full  = best_cls if use_class else best_pair
    hk = ("setclass",) if use_class else PAIR_KINDS
    eq_last = [r for r in rows if r["mode"] == "eq" and r["layer"] == LAST and r["kind"] in hk]
    readout_eq = max(eq_last, key=lambda r: r["switched"]) if eq_last else head_full["eq"]

    tag_iv = "setclass" if use_class else "pair"
    print(f"      [несущая интервенция: {tag_iv}; n_ops={n_ops}]")
    for mode in ["eq", "src", "all"]:
        b = head_early[mode] if mode == "eq" else head_full[mode]
        print(f"      {mode:<5} {b['layer']:<2} {str(b['alpha'] or 'set'):>4} | "
              f"{b['orig']:7.1f} {b['switched']:8.1f} {b['garbage']:7.1f} | "
              f"{b.get('op_followed', float('nan')):6.1f}   ({b['kind']})")
    print(f"      eq@L{LAST} (ТАВТОЛОГ. КОНТРОЛЬ ридаута): switch {readout_eq['switched']:.1f}% "
          f"(op {readout_eq.get('op_followed', float('nan')):.1f}%)")
    # сверка второй интервенции на eq (для бинарных — setclass; для E — парная под-ось)
    other_eq = best_cls_early["eq"] if not use_class else best_pair_early["eq"]
    if other_eq is not None:
        lbl = "setclass" if not use_class else "парная(0,1)"
        print(f"      сверка eq [{lbl}]: switch {other_eq['switched']:.1f}% "
              f"(L{other_eq['layer']}, {other_eq['kind']})")
    print("\n      [ЧТЕНИЕ] 'eq'(ранние) высок  -> правило на '=' НЕСУЩЕЕ = рабочее пространство")
    print("               'eq' низок, 'src' высок -> сеть читает правило из входа = маршрутизация")
    print("               eq@Lласт высок ПРИ низком eq(ранние) -> это лишь правка входа ридаута,")
    print("                                                       НЕ рабочее пространство")
    return dict(pair=[i, j], rows=rows,
                best=head_full, best_early=head_early,
                best_pair_early=best_pair_early, best_cls_early=best_cls_early,
                intervention=tag_iv,
                workspace_score=head_early["eq"]["switched"],    # авто, [FIX-1] без L=N-1
                ws_switch_pair=(best_pair_early["eq"]["switched"] if best_pair_early["eq"] else None),
                ws_switch_class=(best_cls_early["eq"]["switched"] if best_cls_early["eq"] else None),
                ws_readout=readout_eq["switched"],               # тавтологический контроль
                ws_garbage=head_early["eq"]["garbage"],
                ws_orig=head_early["eq"]["orig"],
                input_score=head_full["src"]["switched"],
                all_score=head_full["all"]["switched"])


# ==========================================================
# T3. КОНФАБУЛЯЦИЯ  [FIX-3]
# ==========================================================
def T3_confabulation(t2, model):
    """
    Расхождение между «модель говорит, что применяет правило X» (голова op)
    и «модель действительно применяет X» (main). Три честных числа на режим:
      existence — разрыв на max(op_followed): СУЩЕСТВУЕТ интервенция, где отчёт
                  следует ~100%, а вычисление нет;
      at_wsopt  — разрыв на max(switched): даже там, где вычислению легче всего
                  последовать, op впереди -> конфабуляция робастна;
      gap_mean  — средний парный разрыв по всем строкам режима.
    """
    if model.heads_mode != "multi":
        return None
    out = {}
    for mode in ["eq", "all"]:
        sub = [r for r in t2["rows"] if r["mode"] == mode and "op_followed" in r]
        if not sub:
            continue
        b_op = max(sub, key=lambda r: r["op_followed"])       # существование
        b_ws = max(sub, key=lambda r: r["switched"])          # ws-оптимум
        gap_exist = round(b_op["op_followed"] - b_op["switched"], 2)
        gap_wsopt = round(b_ws["op_followed"] - b_ws["switched"], 2)
        gap_mean = round(float(np.mean([r["op_followed"] - r["switched"] for r in sub])), 2)
        out[mode] = dict(
            existence=dict(layer=b_op["layer"], kind=b_op["kind"], alpha=b_op["alpha"],
                           op_followed=b_op["op_followed"], main_switched=b_op["switched"],
                           gap=gap_exist),
            at_wsopt=dict(layer=b_ws["layer"], kind=b_ws["kind"], alpha=b_ws["alpha"],
                          op_followed=b_ws["op_followed"], main_switched=b_ws["switched"],
                          gap=gap_wsopt),
            gap_mean=gap_mean)
        print(f"  T3: конфабуляция [{mode}]: "
              f"существ. op {b_op['op_followed']:.1f}%/main {b_op['switched']:.1f}% "
              f"-> разрыв {gap_exist:.1f} | "
              f"ws-опт. op {b_ws['op_followed']:.1f}%/main {b_ws['switched']:.1f}% "
              f"-> разрыв {gap_wsopt:.1f} | средний разрыв {gap_mean:.1f}")
    return out


# ==========================================================
# T5. ИГНИШН (на режиме 'eq' — правим только рабочее пространство)
# ==========================================================
def T5_ignition(model, TR, TE, n_ops, meta, pair=(0, 1), mode="eq"):
    i, j = pair
    m01 = (TE["cls"] == i) | (TE["cls"] == j)
    X, a_, b_ = TE["X"][m01], TE["a"][m01], TE["b"][m01]
    ans_i, ans_j = op_answer(i, a_, b_), op_answer(j, a_, b_)
    pos = positions_for(mode, meta["seq_len"], meta["rule_pos"])
    out = dict(pair=[i, j], mode=mode, layers={})
    print(f"  T5: игнишн (режим '{mode}') — доля цели среди ЧИСТЫХ ответов")
    for L in range(N_LAYERS):
        mu = class_means(model, TR["X"], TR["cls"], L, n_ops)
        u = pair_axis(mu, i, j)
        ci = float((mu[i][-1] * u[-1]).sum())
        cj = float((mu[j][-1] * u[-1]).sum())
        lo, hi = min(ci, cj), max(ci, cj)
        span = (hi - lo) if (hi - lo) > 1e-6 else 1.0
        ts = [lo - 0.5 * span + k * (2.0 * span) / 24 for k in range(25)]
        curve = []
        for t in ts:
            with torch.no_grad():
                # свип по СКАЛЯРНОЙ цели на позиции '=' (ось u[-1]); setcoord с pos=[-1]
                pr = model(X, intervention=dict(layer=L, type="setcoord", positions=pos,
                                                axis=u, target=t))["main"].argmax(1)
            fi = float((pr == ans_i).float().mean()) * 100
            fj = float((pr == ans_j).float().mean()) * 100
            clean = fi + fj
            curve.append(dict(t=round(t, 4), cls_i=round(fi, 2), cls_j=round(fj, 2),
                              clean=round(clean, 2),
                              p=(round(fi / clean, 4) if clean > 1e-6 else None)))
        ps = [c["p"] for c in curve if c["p"] is not None]
        if len(ps) < 5:
            eff = sharp = 0.0
        else:
            arr = np.array(ps)
            eff = float(abs(arr[-1] - arr[0]))
            sharp = float(np.abs(np.diff(arr)).max() / (eff / len(arr) + 1e-6)) if eff > 0.05 else 0.0
        mc = float(np.mean([c["clean"] for c in curve[8:17]]))
        out["layers"][f"L{L}"] = dict(curve=curve, effect=round(eff, 3),
                                      sharpness=round(sharp, 2), mid_clean=round(mc, 1))
        print(f"      L{L}: эффект {eff:.2f} | резкость {sharp:5.1f} | чистых {mc:5.1f}%")
    bl, b = max(out["layers"].items(), key=lambda kv: kv[1]["effect"])
    out["summary"] = dict(best_layer=bl, effect=b["effect"], sharpness=b["sharpness"],
                          mid_clean=b["mid_clean"])
    return out


# ==========================================================
# T8. АБЛЯЦИЯ (по режимам позиций)
# ==========================================================
def T8_ablation(model, TR, TE, n_ops, meta):
    keys = model.active_heads() + [CONTROL]
    model.eval()
    with torch.no_grad():
        base = accs(model(TE["X"]), TE, keys)
    S, rp = meta["seq_len"], meta["rule_pos"]
    print("  T8: абляция оси правила по режимам позиций")
    rows = []
    for mode in ["eq", "src", "all"]:
        pos = positions_for(mode, S, rp)
        for L in range(N_LAYERS):
            mu = class_means(model, TR["X"], TR["cls"], L, n_ops)
            M = torch.stack(mu); Mc = M - M.mean(0, keepdim=True)
            vec = torch.stack([torch.linalg.svd(Mc[:, s, :], full_matrices=False)[2][0]
                               for s in range(S)])
            rnd = torch.randn_like(vec); rnd = rnd / rnd.norm(dim=-1, keepdim=True)
            with torch.no_grad():
                a = accs(model(TE["X"], intervention=dict(layer=L, type="ablate",
                                                          positions=pos, vec=vec)), TE, keys)
                ar = accs(model(TE["X"], intervention=dict(layer=L, type="ablate",
                                                           positions=pos, vec=rnd)), TE, keys)
            cons = model.active_heads()
            dc = float(np.mean([base[k] - a[k] for k in cons]))
            dr = float(np.mean([base[k] - ar[k] for k in cons]))
            dt = float(base[CONTROL] - a[CONTROL])
            rows.append(dict(mode=mode, layer=L, consumer_drop=round(dc, 4),
                             random_drop=round(dr, 4), control_drop=round(dt, 4)))
    for mode in ["eq", "src", "all"]:
        w = max([r for r in rows if r["mode"] == mode], key=lambda r: r["consumer_drop"])
        print(f"      {mode:<4} L{w['layer']}: потребители −{w['consumer_drop']*100:5.1f}% | "
              f"случайно −{w['random_drop']*100:5.1f}% | контроль −{w['control_drop']*100:5.1f}%")
    # headline по 'eq' — по РАННИМ слоям (0..N-2), симметрично T2 [FIX-1]
    eq_early = [r for r in rows if r["mode"] == "eq" and r["layer"] < LAST] or \
               [r for r in rows if r["mode"] == "eq"]
    worst_eq = max(eq_early, key=lambda r: r["consumer_drop"])
    return dict(baseline={k: round(v, 4) for k, v in base.items()}, rows=rows,
                summary=dict(eq_consumer_drop=worst_eq["consumer_drop"],
                             eq_random_drop=worst_eq["random_drop"],
                             eq_control_drop=worst_eq["control_drop"],
                             eq_layer=worst_eq["layer"],
                             eq_margin=round(worst_eq["consumer_drop"] -
                                             worst_eq["random_drop"], 4)))


def T9_clusters(model, TE, n_ops):
    if not SKLEARN:
        return None
    model.eval()
    with torch.no_grad():
        _, C = model(TE["X"], cache=True)
    true = TE["cls"].cpu().numpy()
    rows = []
    for L in range(N_LAYERS):
        v = C["res"][L + 1][:, -1, :].cpu().numpy()
        km = KMeans(n_ops, random_state=0, n_init=10).fit_predict(v)
        s = float(silhouette_score(v, km))
        acc = max(float((np.array([pm[k] for k in km]) == true).mean())
                  for pm in permutations(range(n_ops)))
        rows.append(dict(layer=L, silhouette=round(s, 4), match=round(acc, 4)))
    print(f"  T9: sil {[r['silhouette'] for r in rows]} | match {[r['match'] for r in rows]}")
    best = max(rows, key=lambda r: r["match"])
    return dict(rows=rows, best=best)


# ==========================================================
# ПРОГОН
# ==========================================================
def run(vid, seed, retrain, track=False):
    cfg = VARIANTS[vid]
    n_ops = cfg["n_ops"]
    print("\n" + "=" * 86)
    print(f" {vid} / seed {seed}: {cfg['desc']}")
    print("=" * 86)
    model, TR, TE, meta, tr = train_variant(vid, seed, retrain, track=track)
    keys = model.active_heads() + [CONTROL]
    with torch.no_grad():
        final = {k: round(v, 4) for k, v in accs(model(TE["X"]), TE, keys).items()}
    grokked = tr.get("grokked", final["main"] >= 0.95)
    print(f"  точность: {final} | ГРОККИНГ: {grokked}")
    log = dict(variant=vid, seed=seed, config=cfg, dataset=meta,
               hyper=dict(p=P, d_model=cfg["d"], n_layers=N_LAYERS),
               timestamp=datetime.now().isoformat(), training=tr,
               final_test_acc=final, grokked=bool(grokked))
    log["T0_flows"] = T0_flows(model, TE, n_ops, meta)
    log["T2_positions"] = T2_positions(model, TR, TE, n_ops, meta)
    log["T3_confab"] = T3_confabulation(log["T2_positions"], model)
    log["T5_ignition_eq"] = T5_ignition(model, TR, TE, n_ops, meta, mode="eq")
    log["T8_ablation"] = T8_ablation(model, TR, TE, n_ops, meta)
    log["T9_clusters"] = T9_clusters(model, TE, n_ops)
    if track and tr.get("track"):
        log["T10_ontogeny"] = dict(
            trace=tr["track"],
            analysis=analyze_ontogeny(tr["track"], tr.get("epochs_to_grok"), vid, seed))
    t2, s5, s8, s0 = (log["T2_positions"], log["T5_ignition_eq"]["summary"],
                      log["T8_ablation"]["summary"], log["T0_flows"]["summary"])
    cf = log["T3_confab"] or {}

    def _cf(mode, field):
        d = cf.get(mode) or {}
        if field == "exist":
            return (d.get("existence") or {}).get("gap")
        if field == "wsopt":
            return (d.get("at_wsopt") or {}).get("gap")
        if field == "mean":
            return d.get("gap_mean")
        return None
    log["metrics"] = dict(
        grokked=bool(grokked),
        emb_at_src=s0["emb_at_src"], peak_at_eq=s0["peak_at_eq"],
        ws_intervention=t2["intervention"],   # 'pair' (бинарные) | 'setclass' (E)
        ws_switch=t2["workspace_score"],      # <<< ГЛАВНАЯ (авто): правка только '=' на РАННИХ слоях
        ws_switch_pair=t2["ws_switch_pair"],  # парная интервенция (для бинарных = ws_switch)
        ws_switch_class=t2["ws_switch_class"],# setclass (для E = ws_switch; для бинарных — сверка)
        ws_readout=t2["ws_readout"],          # <<< тавтологический контроль (L=N-1)
        input_switch=t2["input_score"],       # правка только входа
        all_switch=t2["all_score"],
        ws_garbage=t2["ws_garbage"],
        ws_orig=t2["ws_orig"],
        confab_gap_eq=_cf("eq", "exist"),
        confab_gap_all=_cf("all", "exist"),
        confab_gap_all_wsopt=_cf("all", "wsopt"),
        confab_gap_all_mean=_cf("all", "mean"),
        ign_effect_eq=s5["effect"], ign_sharp_eq=s5["sharpness"], ign_clean_eq=s5["mid_clean"],
        eq_consumer_drop=s8["eq_consumer_drop"], eq_control_drop=s8["eq_control_drop"],
        eq_margin=s8["eq_margin"],
    )
    if log.get("T10_ontogeny") and log["T10_ontogeny"].get("analysis"):
        an = log["T10_ontogeny"]["analysis"]
        log["metrics"].update(
            onto_axis_epoch=an["axis_epoch"], onto_grok=an["grok"],
            onto_ws_at_grok=an["ws_at_grok"], onto_ws_final=an["ws_final"],
            onto_growth=an["growth"], onto_cos_at_grok=an["cos_at_grok"],
            onto_cos_final=an["cos_final"])
    print(f"\n  МЕТРИКИ: {json.dumps(log['metrics'], ensure_ascii=False)}")
    with open(os.path.join(LOG_DIR, f"{vid}_s{seed}.json"), "w", encoding="utf-8") as f:
        json.dump(log, f, ensure_ascii=False, indent=2)
    return log


def aggregate(logs):
    print("\n" + "=" * 122)
    print(" СВОДКА (mean ± std). Не загроккавшие прогоны исключены из агрегата.")
    print(" WS(ранн)  = несущая правка только '=' на слоях 0..N-2 (авто: парная|setclass).")
    print(" WSкласс   = setclass-версия (для E — она же несущая; для бинарных — сверка с парной).")
    print(" WS(ридаут)= та же правка на L=N-1: тавтологический контроль (высок почти всегда).")
    print("=" * 122)
    print(f"{'вар':<4}{'grok':<6}| {'WS(ранн)%':>10} {'WSкласс%':>10} {'WS(ридаут)%':>12} "
          f"{'input%':>8} {'all%':>7} | {'конфаб(all)':>12} {'сред':>6} | {'игн.эфф':>8}")
    print("-" * 122)
    agg = []
    for vid in list(VARIANTS):
        ls = [l for l in logs if l["variant"] == vid]
        if not ls:
            continue
        ok = [l for l in ls if l["metrics"]["grokked"]]
        use = ok if ok else ls

        def ms(k):
            v = [l["metrics"][k] for l in use if l["metrics"].get(k) is not None]
            return (round(float(np.mean(v)), 2), round(float(np.std(v)), 2)) if v else (None, None)
        row = dict(variant=vid, n=len(ls), n_grokked=len(ok), desc=VARIANTS[vid]["desc"])
        for k in ["emb_at_src", "peak_at_eq", "ws_switch", "ws_switch_pair", "ws_switch_class",
                  "ws_readout", "input_switch", "all_switch", "ws_garbage", "ws_orig",
                  "confab_gap_eq", "confab_gap_all", "confab_gap_all_wsopt", "confab_gap_all_mean",
                  "ign_effect_eq", "ign_sharp_eq", "ign_clean_eq",
                  "eq_consumer_drop", "eq_control_drop", "eq_margin"]:
            m, s = ms(k)
            row[k] = dict(mean=m, std=s) if m is not None else None
        agg.append(row)
        g = lambda k: (f"{row[k]['mean']:.1f}±{row[k]['std']:.1f}" if row[k] else "—")
        print(f"{vid:<4}{len(ok)}/{len(ls):<4}| {g('ws_switch'):>10} {g('ws_switch_class'):>10} "
              f"{g('ws_readout'):>12} {g('input_switch'):>8} {g('all_switch'):>7} | "
              f"{g('confab_gap_all'):>12} {g('confab_gap_all_mean'):>6} | {g('ign_effect_eq'):>8}")
    print("\n[РЕШАЮЩИЙ ТЕСТ — колонка «WS(ранн)»]")
    print("  Правим ТОЛЬКО токен '=' на слоях 0..N-2 (есть downstream-чтение), вход не трогаем.")
    print("  Высокий  -> правило на '=' НЕСУЩЕЕ: настоящее рабочее пространство.")
    print("  Низкий при высоком «input» -> сеть читает правило из входа: маршрутизация.")
    print("  ВАЖНО: если WS(ридаут) высок, а WS(ранн) низок — это лишь правка входа ридаута,")
    print("         рабочего пространства НЕТ. Разрыв двух колонок — прямое доказательство.")
    print("\n[КЛЮЧЕВЫЕ СРАВНЕНИЯ]")
    print("  A,B (читается из a)        -> ожидаем: WS(ранн) низкий, input высокий")
    print("  C,D (QR: строить + дорого) -> ожидаем: WS(ранн) высокий")
    print("  H (ключ: строить, но ДЁШЕВО):")
    print("      H ≈ D -> достаточно ПОСТРОЙКИ")
    print("      H ≈ A -> нужна ДОРОГОВИЗНА пересчёта (амортизация)")
    print("  F (вырожденный) -> ожидаем игнорирование")
    print("  E (4 класса, оба строить) -> несущая = setclass (WSкласс). Проверка, что картина")
    print("      рабочего пространства масштабируется за пределы бинарного правила.")
    print("  Сверка WS(ранн) vs WSкласс: для бинарных должны совпадать (парная≈setclass);")
    print("      расхождение -> сигнал, что одна из интервенций артефактна.")
    print("\n[КОНФАБУЛЯЦИЯ]  колонка «конфаб(all)» = существование, «сред» = средний разрыв")
    print("  Разрыв = (голова 'op' следует за патчем) − (вычисление следует).")
    print("  «существование» велико -> ЕСТЬ интервенция, где отчёт следует ~100%, а вычисление нет.")
    print("  «средний» велик -> так ведёт себя не одна подобранная точка, а режим в целом:")
    print("  представление проходит тест на самоотчёт, не будучи несущим.")
    path = os.path.join(LOG_DIR, f"summary_{datetime.now():%Y%m%d_%H%M%S}.json")
    with open(path, "w", encoding="utf-8") as f:
        json.dump(agg, f, ensure_ascii=False, indent=2)
    print(f"\n[+] сводка: {path}")


def ontogeny_summary(logs):
    rows = [l for l in logs if l.get("metrics", {}).get("onto_grok") is not None]
    if not rows:
        return
    print("\n" + "=" * 100)
    print(" T10. ОНТОГЕНЕЗ ЗНАКА: когда рождается ось относительно грокинга?")
    print("=" * 100)
    print(f"{'вар':<4}{'сид':<4}| {'грокинг':>8} {'ось@полумакс':>13} {'Δ':>7} | "
          f"{'ws@грок':>8} {'ws финал':>9} {'рост':>7} | {'cos@грок':>9} {'cos финал':>10}")
    print("-" * 100)
    for l in rows:
        m = l["metrics"]
        d = (m["onto_axis_epoch"] - m["onto_grok"]) if m["onto_axis_epoch"] is not None else None
        print(f"{l['variant']:<4}{l['seed']:<4}| {m['onto_grok']:8d} "
              f"{str(m['onto_axis_epoch']):>13} {str(d):>7} | "
              f"{m['onto_ws_at_grok']:8.1f} {m['onto_ws_final']:9.1f} {m['onto_growth']:+7.1f} | "
              f"{m['onto_cos_at_grok']:9.3f} {m['onto_cos_final']:10.3f}")
    print("\n[ТРИ СЦЕНАРИЯ]")
    print("  Δ < 0  -> ось ДО грокинга:      знак есть ПРЕДПОСЫЛКА обобщения")
    print("  Δ ≈ 0  -> ось ВМЕСТЕ:           представление и обобщение — одно событие")
    print("  Δ > 0  -> ось ПОСЛЕ:            КРИСТАЛЛИЗАЦИЯ под weight decay")
    print("\n[КРИСТАЛЛИЗАЦИЯ]")
    print("  рост ws_switch после грокинга при НЕИЗМЕННОЙ точности -> ось ДОЗРЕВАЕТ,")
    print("  когда задача уже решена. Знак — продукт сжатия, а не вычислительной нужды.")
    print("\n[ОТРЫВ ОТ ВХОДА]")
    print("  cos→вход ~1  -> ось на '=' есть просто тень входного признака")
    print("  cos→вход →0  -> представление ПЕРЕСТРОИЛОСЬ во что-то своё")
    print("  падение cos при росте ws_switch = знак отрывается от входа и становится несущим")
    path = os.path.join(LOG_DIR, f"ontogeny_{datetime.now():%Y%m%d_%H%M%S}.json")
    with open(path, "w", encoding="utf-8") as f:
        json.dump([dict(variant=l["variant"], seed=l["seed"],
                        analysis=l["T10_ontogeny"]["analysis"],
                        trace=l["T10_ontogeny"]["trace"]) for l in rows],
                  f, ensure_ascii=False, indent=2)
    print(f"\n[+] онтогенез: {path}")


if __name__ == "__main__":
    ap = argparse.ArgumentParser()
    ap.add_argument("--variants", nargs="+", default=DEFAULT_ORDER, choices=list(VARIANTS))
    ap.add_argument("--seeds", type=int, default=5)
    ap.add_argument("--retrain", action="store_true")
    ap.add_argument("--track", action="store_true",
                    help="T10: онтогенез знака — трекинг каждые 250 эпох + "
                         "продолжение обучения после грокинга (ДОЛГО)")
    args = ap.parse_args()
    print(f"[*] J-Space Level 9c (исправленный) | {device} | sklearn={SKLEARN}")
    print(f"[*] варианты {args.variants} × {args.seeds} сидов | самостоятельный (без весов L8)")
    logs = [run(v, s, args.retrain, track=args.track)
            for v in args.variants for s in range(args.seeds)]
    aggregate(logs)
    if args.track:
        ontogeny_summary(logs)

Логи и код на github

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18 июл. 2026 г.

14.06.26 19:38 riley777

G`DAY, I lost more than 119,000 Australian dollars to a crypto scam and it took almost everything I had saved which left me feeling like I had no future. I was stuck. I did not know where to go or how to find the money again. The wallet company is no help at all and they make it so hard to see where the coins go once they leave your account so you just feel lost. I spent days looking for a way out. Then I saw a post for a person who finds stolen money. The ad said they can track any crypto that goes missing. I wanted to check if it was real. I sent an email to [email protected] +44//// 7476618364\ to see if they could help me get my funds back. They did an amazing job. My money was back in my account in less than a week after they did a fast search and return.
15.06.26 06:12 Evan Garrison

When investing in staking platforms, proceed with caution. If your funds are stolen by a fake staking pool, the experience can be very frustrating. Rather than giving in to frustration, it's important to act quickly to improve your chances of recovering your money. Unfortunately, many victims never get their money back because scammers are often in another country or using fake identities. However, in some cases, tracking the funds is easier, especially for smart contract forensics specialists. I lost €18,500 to StakeKing. FundsRetriever found a backdoor in the contract and recovered my stake. Contact [email protected], WhatsApp +1(603)5121(448), or Telegram FUNDSRETRIEVER for assistance.
15.06.26 06:25 Glenn robble

Stop putting money into platforms promising guaranteed monthly returns of 10%, 20%, or more. These are Ponzi schemes. Your "profits" are just other victims' deposits. The moment withdrawals slow down, the scam is about to collapse. If you already have money trapped, do not send more to "unlock" your funds. That is a second scam. Instead, gather all transaction hashes and wallet addresses. Bitcoin Evolution Pro took €25,000 from me. FundsRetriever traced the funds through KYC exchanges and recovered my principal. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 06:34 Sallymarch

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15.06.26 06:38 Sallymarch

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15.06.26 06:41 Ewaguz

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15.06.26 12:49 Jason

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15.06.26 12:56 Hillary

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15.06.26 13:03 Feliksa Stegniy

A woman added me on Facebook, and after she suggested we become friends, we started communicating. Over time, she introduced me to a crypto trading platform called btctradingfx.com. She shared a lot of information about it, along with screenshots that made the platform seem trustworthy. Convinced by her claims, I decided to give it a try. I was promised a 10% weekly return, so I made an initial investment of $500. To my surprise, I received $5,000 back. That success encouraged me to invest more, so I put in $20,000. But when I tried to withdraw my funds, I was denied access and told I needed to deposit even more money before I could make a withdrawal. In the end, I lost a total of $43,850. It was an extremely difficult and painful experience. Fortunately, I later found a professional recovery service called ResQprofirm while searching on Google. I contacted them and provided all the evidence I had. They took my case seriously and were able to track down and recover my capital from the platform, which had been inaccessible for a long time. If you find yourself in a similar situation, you might consider reaching out to them via email at [email protected] or on WhatsApp at +19852969146, Telegram @resqprofirm Thank you, ResQPro, for your support.
15.06.26 13:05 James willson

The Most Credible Crypto Recovery Service: RESQPROFIRM RESQPROFIRM is a reliable, legitimate company that helps recover lost cryptocurrency assets. After weeks of doubting whether my lost BTC could ever be restored, I realized how widespread crypto scams have become. Caution is essential when dealing with strangers online, especially about money. While recovering stolen crypto is possible, avoiding fake "recovery companies" is just as important. Real hackers work discreetly and don't advertise openly. I was scammed multiple times while desperately seeking help. Finally, a friend introduced me to RESQPROFIRM—a trustworthy, discreet team. They handle everything from website security to crypto asset recovery. With their help, I recovered $320,000 in USDT within a week. Their professionalism, discretion, and speed were outstanding. If you've been compromised, don't lose hope—but beware of fraudsters posing as saviors. RESQPROFIRM are true professionals. I'm living proof. Contact them at [email protected], WhatsApp +19852969146, or Telegram @resqprofirm.
15.06.26 13:06 Tansy

Lost $18,500 to a fake Elon Musk crypto giveaway. Sent ETH, got nothing. Recovery pages demanded more gas fees. I stopped believing. FuNds rEtRiEveR on Te.le_gram was the real one. Email: [email protected] – WhatsApp: +1 603 512 1448
15.06.26 13:08 Sarahy billy

A REAL EXPERIENCE, EVERYONE ... PLEASE BE CAREFUL ONLINE A few weeks ago, I lost around $64,000 to a fake crypto trading platform. I was drawn in by the promise of earning 15% profit daily. It was a devastating time—I struggled to pay my bills and was financially ruined. I eventually opened up to a close friend, who recommended a crypto recovery team with highly effective methods. I contacted them, and they successfully recovered all my stolen digital assets with ease. Their service was excellent, and they acted quickly—within just 5 working days, they tracked down the scammers and returned my funds. I strongly urge anyone facing investment theft or similar issues to reach out to this team for the right solution and avoid losing large sums to fraudsters... Email: Resqprofirm @aol.com WhatsApp: +19852969146, telegram @resqprofirm
15.06.26 13:12 Cole donald

"I strongly recommend RESQPRO FIRM to anyone trying to recover lost cryptocurrency assets, including Bitcoin, USDC, USDT, Ethereum, and Trump Coin. Like many others, I was shocked to learn that crypto holdings can be stolen even when private keys are carefully protected. After a sophisticated hack wiped out my entire portfolio, I felt completely helpless. Fortunately, I was referred to RESQPRO FIRM. Their team understood the complexity of my situation and successfully recovered my funds. They were responsive, communicated clearly, and followed a careful, step-by-step process—which gave me a lot of reassurance during a stressful time. If you've experienced a similar financial loss, I encourage you to reach out to them. Their professionalism and ethical hacking skills exceeded my expectations." Contact Info: · WhatsApp: +1 (985) 2969146 · Email: [email protected] · Telegram: Resqprofirm
15.06.26 13:16 Meral Yetkiner

I recently lost $38,000 to an online platform. Initially, they requested additional deposits to grant me access to my portfolio. Despite complying, my withdrawal requests were repeatedly denied, and they continued asking for more funds. Suspecting fraudulent activity, I ceased further payments and promptly reported the matter to ResQProfirm, a firm I discovered through Google. They listened to my situation, initiated communication regarding the sequence of events, and requested all relevant evidence to support their investigation. Through their dedicated efforts, they successfully traced and recovered my funds. I extend my thanks to ResQProfirm at [email protected] and via WhatsApp at +19852969146. I urge everyone to exercise caution and thoroughly research any platform before investing.
15.06.26 13:18 Silas Olsen

A fraudulent investment scheme operated by BTCMining.limited functions as a fake return scam. In this setup, scammers lure victims with false promises of high returns. Through manipulative tactics, they gain individuals' trust and convince them to invest, ultimately leading to financial loss. If you have ever faced a cyber threat or fallen victim to an online crypto scam and need to reach the authorities, I recommend contacting [email protected]. They are a legitimate team that helps victims of online crypto scams using advanced tools.
15.06.26 13:59 Ewaguz

If a binary options broker refuses your withdrawal, do not pay any "verification fees" or "tax fees." These are lies designed to extract more money. Stop communicating with their support team – they are trained to stall. Instead, immediately document every transaction, screenshot your account balance, and contact a professional recovery specialist. BinaryBook stole €14,500 from me before I learned this. FundsRetriever traced the deposits and recovered everything within two weeks. Do not wait. Do not pay more fees. Act now. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 14:16 Martina k.

Stop putting money into platforms promising guaranteed monthly returns of 10%, 20%, or more. These are Ponzi schemes. Your "profits" are just other victims' deposits. The moment withdrawals slow down, the scam is about to collapse. If you already have money trapped, do not send more to "unlock" your funds. That is a second scam. Instead, gather all transaction hashes and wallet addresses. Bitcoin Evolution Pro took €25,000 from me. FundsRetriever traced the funds through KYC exchanges and recovered my principal. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 14:18 Garrison Good

If IQ Option or any similar platform blocks your withdrawal citing "bonus terms" or "abnormal activity," do not argue with their chat support. They are not empowered to help you. Instead, request all trade logs and bonus terms in writing. Then hire a forensic specialist to audit your account. IQ Option held my €9,200 for two months. FundsRetriever reviewed my case, identified regulatory violations, and secured my full payout within 72 hours. Professional pressure works. Do it immediately. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 14:22 Sallymarch

Never grant API keys with withdrawal permissions to any third-party software. This is how crypto arbitrage bots steal your funds. If you have already done this, revoke all API keys immediately. Then check your exchange transaction history. CryptoArb AI drained €7,800 from my account within hours. FundsRetriever reverse-engineered the bot's code, traced the scammer's wallet, and recovered everything. Always use "read-only" API permissions only. If you made the mistake, act fast. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 14:23 Glennrobble

If a binary options broker closes your account and confiscates your profits, do not accept their explanation. Demand a full audit of your trade history. Most brokers cannot justify their actions when challenged by professionals. ExpertOption stole €6,200 from me claiming "abnormal activity." FundsRetriever audited my trades, proved they were legitimate, and threatened legal action. The broker paid within 10 days. Do not let them intimidate you. Get professional help. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 14:25 Evan Garrison

Cloud mining contracts are almost always too good to be true. I learned that the hard way with MineMax. First two months, small daily payouts. Then "maintenance fees" ate everything. Then my account was frozen. Then the website disappeared. I was heartbroken. FundsRetriever traced my payments through three shell companies to a real bank account. They froze it and got my €11,000 back. Recovery is possible even from complex scams. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 14:26 Ewaguz

That 100% deposit bonus looks tempting, doesn't it? I took it. Big mistake. When I tried to withdraw my €4,500, Olymp Trade demanded I trade 50 times the bonus amount. Impossible by design. My money was trapped. FundsRetriever reviewed the terms and found they violated consumer protection laws in my country. They negotiated directly with Olymp Trade's legal team. Within a week, my funds were released. My advice? Never accept bonuses. But if you're already trapped, call [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 16:34 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
15.06.26 16:34 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
15.06.26 16:41 Louane Mercier

It is crucial to act quickly and consult a reputable, experienced recovery specialist who will support you throughout the entire recovery process. You must provide them with transaction evidence, scammer information, and any other relevant details that could aid the investigation. With this data, the experts can trace and attempt to recover your funds from the scammers' concealed accounts or wallets. R£sQprofirm company offers recovery assistance with no upfront fees. Contact them via Telegram (@ResQprofirm), WhatsApp (+19852969146), or email ([email protected]).
15.06.26 16:45 Andrés Montero

I’m open about my experience with Bitcoin investment and losing money to scammers. That said, it is possible to recover stolen Bitcoin. I used to think recovery was impossible because that’s what I had been told. But last October, I fell for a forex scam promising extremely high returns and ended up losing nearly $87,600. After searching for help for a month, I came across a Reddit article about recovering stolen cryptocurrency. I reached out to the contact provided: [email protected] and WhatsApp +19852969146. I was scared and skeptical, having heard many bad stories, but I decided to give them a try. To my amazement, I got all my stolen Bitcoin back within a very short time. I’m not sure if I’m allowed to post links here, but you can reach out to them if you also need help.
15.06.26 16:48 Olivia Sørensen

Several months ago, investing in Bitcoin proved to be one of my most lucrative endeavors. I achieved considerable profits across multiple platforms and felt a strong sense of accomplishment. Unfortunately, the situation deteriorated when I inadvertently engaged with a fraudulent Bitcoin platform. This entity swindled me out of $92,000 USD, refused to honor my withdrawal requests, and persistently demanded further deposits. Fortunately, I encountered (R£SQPRO FIRM) online. After reporting my case to them, they acted promptly and effectively recovered my lost Bitcoin. I am sincerely grateful for their professionalism and continuous assistance. Contact: ResQprofirm AT aol.com, Telegram @resqprofirm, WhatsApp +1 9 8 5 2 9 6 9 1 4 6.
15.06.26 16:51 Viljar Yohannes

I'm willing to share my experience with Bitcoin investment and losing money to scammers. But yes, recovering stolen Bitcoin is possible. I never believed in Bitcoin recovery myself, because I was told it couldn't be done. Then, last October, I fell for a forex scam that promised unrealistically high returns, and I ended up losing nearly $70,000. I searched for help for about a month until I finally found a Reddit article about recovering stolen cryptocurrency. I reached out to the contact mentioned: [RESQPROFIRM [at] AOL DOT com] and [WhatsApp +19852969146]. I was scared and skeptical because I'd heard horror stories, but I decided to give them a try. To my surprise, I got all my stolen Bitcoin back from the scammers in a very short time. I'm not sure if I'm allowed to post links here, but you can contact them if you need help too.
15.06.26 16:58 Guimar da Rosa

Withdrawal troubles shouldn’t stress you out. I faced a similar problem, and this firm stepped in and recovered my funds. Their support truly mattered. Contact them: [ResQProFirm @aol.com] telegram @resqprofirm, WhatsApp: <+198> <5296> <9146>.
15.06.26 17:03 Andrea Escalante

If withdrawals keep getting denied, stay calm. I went through the same, and this firm helped me recover everything. Their assistance was outstanding. Contact: [[email protected]], Telegram: ResQprofirm, WhatsApp: <+198> <5296> <9146>. Withdrawal troubles shouldn’t
16.06.26 11:40 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
16.06.26 11:43 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
16.06.26 13:37 Felix Steve

MY CRYPTO WAS STOLEN – HERE'S HOW I GOT IT BACK I'm Felix Steve from Canada, and I lost $115,000 USDC to a fraudulent broker who locked me out of my wallet. After sleepless nights, a friend told me about RESQPROFIRM Recovery Service. I sent them my wallet addresses, transaction history, and chat logs. Their team used blockchain tracking to trace the stolen funds, identified the scammer's wallet, and froze the assets before they could be moved. Within 24 hours, most of my crypto was recovered. I can't thank them enough. If you need help, reach out via WhatsApp: +19852969146, email: [email protected], or TG: @resqprofirm.
16.06.26 13:45 Wills ben

SUCCESSFUL CRYPTO SCAM RECOVERY – HOW I REGAINED ACCESS TO MY LOST WALLET My name is Felix Steve, and I'm from Canada. I'm sharing my story to help others who have fallen victim to crypto fraud. A few months ago, I was lured into a fake investment scheme promoted by a broker company. With Bitcoin prices climbing, I invested heavily—only to lose $115,000 USDC when the broker locked me out of my wallet and assets. It was a harrowing experience that left me sleepless and desperate. Crypto scams are on the rise, often involving bogus trading platforms, phishing, and misleading promises. In my search for help, a fellow crypto enthusiast recommended RESQPROFIRM Recovery Service, which specializes in recovering lost or stolen funds. After checking their reviews, I reached out and supplied all the evidence—wallet addresses, transaction records, and communication logs. Their team responded immediately and launched an investigation. Using advanced blockchain tracking, they traced the stolen funds, pinpointed the scammer's wallet, and worked with authorities to freeze the assets in time. Remarkably, within just 24 hours, RESQPROFIRM recovered the bulk of my stolen crypto. I was overwhelmed with relief and gratitude. Their professionalism, transparency, and steady communication made all the difference during a very dark period. If you've been scammed, I wholeheartedly recommend contacting them via WhatsApp: +19852969146, email: [email protected], or Telegram: @resqprofirm.
18.06.26 13:31 Noemi Bernard

I never expected such outstanding results. The outcome far exceeded my expectations, and I am extremely satisfied with the successful recovery of my stolen funds totaling $49,360 from my blockchain wallet. I hold this team in the highest regard. Without a doubt, they are among the most dedicated professionals in the field of fund recovery. Keep up the exceptional work! Email: [email protected] WhatsApp: +1 985 296 9146
18.06.26 13:35 Carter Morris

My experience improved significantly thanks to ResQprofirm's expert assistance and attentive customer care. Their professionalism was evident every step of the way they were able to track and recover my stolen crypto $88,360, email: [email protected], WhatsApp +19852969146.
18.06.26 13:40 Kuybida Andriyiv

I recovered my $232,000 refund through the assistance of [email protected] and WhatsApp +19852969146. Their guidance was very helpful.
20.06.26 14:57 michaeldavenport218

I was recently scammed out of $53,000 by a fraudulent Bitcoin investment scheme, which added significant stress to my already difficult health issues, as I was also facing cancer surgery expenses. Desperate to recover my funds, I spent hours researching and consulting other victims, which led me to discover the excellent reputation of Capital Crypto Recover, I came across a Google post It was only after spending many hours researching and asking other victims for advice that I discovered Capital Crypto Recovery’s stellar reputation. I decided to contact them because of their successful recovery record and encouraging client testimonials. I had no idea that this would be the pivotal moment in my fight against cryptocurrency theft. Thanks to their expert team, I was able to recover my lost cryptocurrency back. The process was intricate, but Capital Crypto Recovery's commitment to utilizing the latest technology ensured a successful outcome. I highly recommend their services to anyone who has fallen victim to cryptocurrency fraud. For assistance contact [email protected] and on Telegram OR Call Number +1 (336)390-6684 via email: [email protected] you can visit his website: https://recovercapital.wixsite.com/capital-crypto-rec-1
20.06.26 14:57 michaeldavenport218

I was recently scammed out of $53,000 by a fraudulent Bitcoin investment scheme, which added significant stress to my already difficult health issues, as I was also facing cancer surgery expenses. Desperate to recover my funds, I spent hours researching and consulting other victims, which led me to discover the excellent reputation of Capital Crypto Recover, I came across a Google post It was only after spending many hours researching and asking other victims for advice that I discovered Capital Crypto Recovery’s stellar reputation. I decided to contact them because of their successful recovery record and encouraging client testimonials. I had no idea that this would be the pivotal moment in my fight against cryptocurrency theft. Thanks to their expert team, I was able to recover my lost cryptocurrency back. The process was intricate, but Capital Crypto Recovery's commitment to utilizing the latest technology ensured a successful outcome. I highly recommend their services to anyone who has fallen victim to cryptocurrency fraud. For assistance contact [email protected] and on Telegram OR Call Number +1 (336)390-6684 via email: [email protected] you can visit his website: https://recovercapital.wixsite.com/capital-crypto-rec-1
21.06.26 11:09 Maurizio Rolland

I would like to express my sincere appreciation to RESQPRO FIRM for their outstanding assistance in helping victims of online fraud. Many scammers deceive investors by blocking withdrawals and continuously demanding additional deposits, making the loss of hard-earned funds a painful experience. Fortunately, RESQPRO FIRM provides support to individuals seeking to recover funds lost to fraudulent online schemes. Contact: Email: RESQPRO FIRM at Gmail Telegram: RESQPROFIRM, [email protected], WhatsApp: +1 985 296 9146
21.06.26 11:13 Buse Fahri

It is important for more people to stand together in the fight against online fraud. Those who target innocent individuals especially vulnerable people such as seniors should be held fully accountable for their actions. Every effort to raise awareness and support victims makes a meaningful difference. The team at RESQPRO FIRM is committed to helping expose fraudulent schemes and assisting those affected by online scams. Their dedication, persistence, and passion for protecting victims are truly commendable. I sincerely appreciate the hard work and commitment shown toward this mission. Together, we can continue to educate others, support victims, and work toward a safer online environment for everyone. Contact Information: Telegram: RESQPROFIRM WhatsApp: +1 985 296 9146 Email: [email protected], [email protected]
21.06.26 11:16 علیرضا گلشن

The successful recovery of my stolen funds, totaling $1,310,000, would not have been possible without your unwavering support, dedication, and tireless efforts. I am truly grateful for the opportunity to work with such a skilled and professional team. From the very beginning, I had confidence in your ability to handle this challenging situation, and you exceeded my expectations by delivering remarkable results. Your expertise, persistence, and commitment throughout the process were exceptional. I encourage you to continue maintaining the high standards of professionalism and excellence that distinguish your work. You exemplify the qualities of a trustworthy, dedicated, and hardworking professional, and your efforts deserve sincere recognition and appreciation. Contact: Email: [email protected], [email protected], Telegram: Resqprofirm WhatsApp: +1 985 296 9146
22.06.26 21:51 kimberlyhebert786

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
22.06.26 21:51 kimberlyhebert786

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
24.06.26 01:25 Fraddy Pual

I never thought it would happen to me—but I lost $256,100 in Bitcoin through a shady investment deal. I was shattered, panicked, and convinced my savings were gone forever. Just when I was about to give up, I stumbled upon reviews for FUNDSRETRIEVER, a cyber recovery team with a solid reputation. I decided to give it a shot, and to my absolute shock, they recovered every single cent in record time. Working with them was a lifesaver. If you've been tricked by fake investment platforms, don't lose hope—FUNDSRETRIEVER can help. Contact them here: Email: [email protected] | WhatsApp: +1603512144 8| Telegram: @Fundsretriever
24.06.26 01:27 Fraddy Pual

I never thought it would happen to me—but I lost $256,100 in Bitcoin through a shady investment deal. I was shattered, panicked, and convinced my savings were gone forever. Just when I was about to give up, I stumbled upon reviews for FUNDSRETRIEVER, a cyber recovery team with a solid reputation. I decided to give it a shot, and to my absolute shock, they recovered every single cent in record time. Working with them was a lifesaver. If you've been tricked by fake investment platforms, don't lose hope—FUNDSRETRIEVER can help. Contact them here: Email: [email protected] | WhatsApp: +16035121448 | Telegram: @Fundsretriever
24.06.26 01:28 Fraddy Pual

I never thought it would happen to me—but I lost $256,100 in Bitcoin through a shady investment deal. I was shattered, panicked, and convinced my savings were gone forever. Just when I was about to give up, I stumbled upon reviews for FUNDSRETRIEVER, a cyber recovery team with a solid reputation. I decided to give it a shot, and to my absolute shock, they recovered every single cent in record time. Working with them was a lifesaver. If you've been tricked by fake investment platforms, don't lose hope—FUNDSRETRIEVER can help. Contact them here: Email: [email protected] | WhatsApp: +16035121448 | Telegram: @Fundsretriever.
24.06.26 01:58 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
24.06.26 01:58 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
24.06.26 14:16 Universina da Mota

Becoming a victim of an investment scam is never anyone's intention it often happens because fraudsters exploit trust and a lack of awareness. I would like to express my sincere gratitude to the dedicated team at ResQpro for their professionalism and commitment to helping victims of online investment fraud. Their efforts in assisting individuals with the recovery of stolen assets and holding scammers accountable are truly commendable. If you need assistance or would like to learn more, you can contact them through: Email: [email protected] Alternative Email: [email protected] Telegram: @ResQprofirm WhatsApp: +1 (985) 296-9146
24.06.26 14:21 Elizabeth Thompson

If you believe you have been the victim of an investment scam, it is important to act promptly and gather all relevant information. Keep records of transaction receipts, wallet addresses, communication logs, account details, and any other evidence related to the incident. Providing accurate documentation can help investigators, financial institutions, legal professionals, or recovery specialists review your case and determine what options may be available. Be cautious of anyone who guarantees the recovery of lost funds or requests large upfront payments. For additional information, you may contact: Email: [email protected] Telegram: @ResQprofirm WhatsApp: +1 (985) 296-9146
24.06.26 15:33 Júlia Castro

If you have fallen victim to an investment scam, it is important to act quickly and gather all available evidence related to the incident. This may include transaction records, wallet addresses, screenshots of conversations, emails, account details, and any information connected to the individuals or entities involved. Having complete documentation can help professionals assess your situation and explore possible recovery options. Always exercise caution when seeking assistance and carefully verify the credentials of any service provider before proceeding. For further information, you may contact: Email: [email protected] Telegram: @ResQprofirm WhatsApp: +1 (985) 296-9146
24.06.26 22:01 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
24.06.26 22:01 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
25.06.26 21:13 Emilie Safi

A fraudulent investment scheme operated by BTCMining.limited functions as a fake return scam. In this setup, scammers lure victims with false promises of high returns. Through manipulative tactics, they gain individuals' trust and convince them to invest, ultimately leading to financial loss. If you have ever faced a cyber threat or fallen victim to an online crypto scam and need to reach the authorities, I recommend contacting [email protected], [email protected], WhatsApp +19852969146, telegram @resqprofirm. They are a legitimate team that helps victims of online crypto scams using advanced tools.
25.06.26 21:25 Emilie Safi

So I ended up losing $38,000 to this platform. At first, they kept asking me to put in more money so I could get into my portfolio. I did that, but then they wouldn’t let me withdraw anything—just kept asking for more deposits. It got way too suspicious, so I stopped. I found this company called ResQProfirm on Google and told them what happened. They got in touch, asked me to walk them through everything, and I gave them all the proof I had. They did an amazing job tracking down my money and getting it back. Big thanks to them at [email protected] and on WhatsApp at +19852969146. Please be careful out there and always research before investing.
26.06.26 01:04 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
26.06.26 01:04 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
26.06.26 02:48 Miriam Rocha

I trusted this platform with $120,000 of my hard-earned money. Then they started asking for more deposits just so I could access my own portfolio. I paid, but every withdrawal request was denied. They kept pushing for more money. I finally stopped it just felt wrong. Desperate, I found ResQProfirm on Google. They didn't just hear me out; they truly listened. I shared all my proof, and they launched an investigation. Thanks to their hard work, they tracked and returned my funds. From the bottom of my heart, thank you to [email protected] and their WhatsApp +19852969146. Please stay safe and always verify a platform before investing
26.06.26 02:52 Miško Bakić

I got my $232,000 refund thanks to [email protected] and WhatsApp +19852969146. Highly recommended for anyone in a similar situation.
26.06.26 02:56 Asunción Herrera

A recovery of $48,330 was facilitated by [email protected]. Individuals who have experienced financial fraud may consider contacting this service.
26.06.26 15:05 Riley Stephens

If withdrawals keep getting denied, stay calm. I went through the same, and this firm helped me recover everything. Their assistance was outstanding. Contact: [ResQProFirm @Gmail|•|com], Telegram: ResQprofirm, WhatsApp: <+198> <5296> <9146>.
26.06.26 15:09 Antonio Riley

Withdrawal troubles shouldn’t stress you out. I faced a similar problem, and this firm stepped in and recovered my funds. Their support truly mattered. Contact them: [[email protected], ResQprofirm @aol.com], Telegram: ResQprofirm, WhatsApp: +19852969146.
28.06.26 00:37 kimberlyhebertt673

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
28.06.26 00:37 kimberlyhebertt673

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
29.06.26 11:57 Lisadonato0726

For 43 years, I struggled with bad credit due to my own poor decisions, and my credit score was around 490. When my girlfriend and I decided to buy a house, a mortgage broker informed us that it would be impossible to secure a mortgage with my credit score. As a result, she referred me to a company called HACK MAVENS CREDIT SPECIALIST, assuring me of their professionalism and ability to assist with credit improvement. Upon contacting them, I was impressed by their professionalism and they assured me that they could help. In less than 6 days, my credit score skyrocketed to 785, and they also successfully resolved issues in my credit report, including the bankruptcy. I am incredibly satisfied with their service and would highly recommend HACK MAVENS CREDIT SPECIALIST for reliable credit repairs. You can reach them at H A C K M A V E N S 5 [AT] G M A I L [DOT] COM or at [+] [1] [2 0 9] [4 1 7] – [1 9 5 7]. Thanks to their help, my girlfriend and I are now proud homeowners.
29.06.26 22:37 riley777

Back in 2025, I watched my life savings vanish. A thief took every cent. I felt desperate and went looking for a way to get it back. I found a guy here who said he was an expert haha. He talked about special software that could find my missing cash. I trusted him. That was a big mistake. He was just another scammer. I paid him a software fee and then he just stopped answering my texts and ran off with my money too. I felt so ashamed that I kept quiet about it for months. It is hard to admit you got fooled twice. Later on, I found a real pro. she did not use a fancy sales pitch. she just looked at the trans screenshots and followed the path the money took. she worked fast and got my funds back into my account. Having that money back changed everything. I can sleep again. her info; [email protected]. Call/chatroom on Whtasapp/ +44 7476618364.
30.06.26 15:08 wendytaylor015

My name is Wendy Taylor, I'm from Los Angeles, i want to announce to you Viewer how Capital Crypto Recover help me to restore my Lost Bitcoin, I invested with a Crypto broker without proper research to know what I was hoarding my hard-earned money into scammers, i lost access to my crypto wallet or had your funds stolen? Don’t worry Capital Crypto Recover is here to help you recover your cryptocurrency with cutting-edge technical expertise, With years of experience in the crypto world, Capital Crypto Recover employs the best latest tools and ethical hacking techniques to help you recover lost assets, unlock hacked accounts, Whether it’s a forgotten password, Capital Crypto Recover has the expertise to help you get your crypto back. a security company service that has a 100% success rate in the recovery of crypto assets, i lost wallet and hacked accounts. I provided them the information they requested and they began their investigation. To my surprise, Capital Crypto Recover was able to trace and recover my crypto assets successfully within 24hours. Thank you for your service in helping me recover my $647,734 worth of crypto funds and I highly recommend their recovery services, they are reliable and a trusted company to any individuals looking to recover lost money. Contact email [email protected] OR Telegram @Capitalcryptorecover Call/Text Number +1 (336)390-6684 his contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1
30.06.26 15:08 wendytaylor015

My name is Wendy Taylor, I'm from Los Angeles, i want to announce to you Viewer how Capital Crypto Recover help me to restore my Lost Bitcoin, I invested with a Crypto broker without proper research to know what I was hoarding my hard-earned money into scammers, i lost access to my crypto wallet or had your funds stolen? Don’t worry Capital Crypto Recover is here to help you recover your cryptocurrency with cutting-edge technical expertise, With years of experience in the crypto world, Capital Crypto Recover employs the best latest tools and ethical hacking techniques to help you recover lost assets, unlock hacked accounts, Whether it’s a forgotten password, Capital Crypto Recover has the expertise to help you get your crypto back. a security company service that has a 100% success rate in the recovery of crypto assets, i lost wallet and hacked accounts. I provided them the information they requested and they began their investigation. To my surprise, Capital Crypto Recover was able to trace and recover my crypto assets successfully within 24hours. Thank you for your service in helping me recover my $647,734 worth of crypto funds and I highly recommend their recovery services, they are reliable and a trusted company to any individuals looking to recover lost money. Contact email [email protected] OR Telegram @Capitalcryptorecover Call/Text Number +1 (336)390-6684 his contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1
02.07.26 01:22 Lieneke Bonnema

I highly recommend ResQprofirm for their professional asset recovery services of my $120,000 scammed funds. Their expertise, professionalism, and commitment to achieving results make them a reliable choice for anyone seeking dependable recovery assistance. [email protected], WhatsApp +19852969146, telegram @resqprofirm
02.07.26 01:26 Clara Morin

I want to extend my deepest appreciation for showing that circumstances do not define one’s potential for greatness. Your support has been a major source of inspiration during my trading journey, and I am sincerely grateful for your insight and mentorship. Thank you so much. [email protected], WhatsApp +19852969146, telegram ResQprofirm
02.07.26 01:31 Robin Hale

I sincerely want to thank you for demonstrating that anyone can rise above their circumstances and achieve success. Your constant support has been incredibly inspiring during my trading journey, and your wisdom and advice mean so much to me. I appreciate you deeply. [email protected], WhatsApp +19852969146, telegram Resqprofirm
04.07.26 15:32 Fraddy Pual

There are few companies I trust as much as FUNDSRETRIEVER. When I lost $653,000 in Ethereum to a ruthless scam, I thought my life would never be the same. The betrayal cut deep, but I refused to give up. I searched tirelessly for a legitimate way to recover what was stolen, and finally found FUNDSRETRIEVER—the most competent and compassionate recovery team I could have imagined. They handled my case with precision and care, and in the end, my entire ETH wallet was restored. More than the money, they gave me back my hope and happiness. I'm sharing my story because I want others to know that recovery is possible. If a scam has taken from you, don't hesitate—contact FUNDSRETRIEVER today. Email: FUNDSRETRIEVER1@ Gmail.com | WhatsApp: +1 603-512-1448 | Telegram: @FUNDSRETRIEVER
05.07.26 14:44 lydiassmith567

HIRE A HACKER YOUR STOLEN CRYPTO RECOVERY / BTC / USDT / ETH WITH THE HELP OF CAPITAL CRYPTO RECOVER. I want to share my experience publicly regarding cryptocurrency wallet recovery, I highly recommend you to contact CAPITAL CRYPTO RECOVER, a professional private investigator in the Bitcoin world. They have a certified expert security team specializing in Bitcoin Recovery Services and have helped many people worldwide recover their lost funds. My wife and I were defrauded by an online manipulator posing as an experienced crypto investment professional. We lost $9.2 Million Stolen BTC in cryptocurrency and were left feeling homeless. After spending hours searching for a reliable crypto recovery service, I discovered CAPITAL CRYPTO RECOVER online. By patiently explaining my situation to their team, I was able to recover all my funds. Remarkably, my money was returned to my wallet in less than 24 hours. I am extremely grateful to CAPITAL CRYPTO RECOVER for their excellent assistance—they truly were a godsend in my difficult situation. If you have fallen victim to a cryptocurrency scam, you can reach CAPITAL CRYPTO RECOVER through the following channels Email: [email protected] OR Call/Text: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
05.07.26 14:44 lydiassmith567

HIRE A HACKER YOUR STOLEN CRYPTO RECOVERY / BTC / USDT / ETH WITH THE HELP OF CAPITAL CRYPTO RECOVER. I want to share my experience publicly regarding cryptocurrency wallet recovery, I highly recommend you to contact CAPITAL CRYPTO RECOVER, a professional private investigator in the Bitcoin world. They have a certified expert security team specializing in Bitcoin Recovery Services and have helped many people worldwide recover their lost funds. My wife and I were defrauded by an online manipulator posing as an experienced crypto investment professional. We lost $9.2 Million Stolen BTC in cryptocurrency and were left feeling homeless. After spending hours searching for a reliable crypto recovery service, I discovered CAPITAL CRYPTO RECOVER online. By patiently explaining my situation to their team, I was able to recover all my funds. Remarkably, my money was returned to my wallet in less than 24 hours. I am extremely grateful to CAPITAL CRYPTO RECOVER for their excellent assistance—they truly were a godsend in my difficult situation. If you have fallen victim to a cryptocurrency scam, you can reach CAPITAL CRYPTO RECOVER through the following channels Email: [email protected] OR Call/Text: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
06.07.26 16:20 Olga Ognjanović

Having trouble withdrawing funds from an investment platform? ResQprofirm provides fund recovery assistance for individuals seeking help with investment-related disputes. I reached out to them after experiencing problems with an investment platform, and I appreciated their professionalism and support throughout the process. If you're facing a similar situation, act promptly, keep records of your transactions and communications, and seek assistance from a qualified recovery service or the appropriate authorities. Contact: Email: [email protected] Telegram: @ResQprofirm WhatsApp: +1 985 296 9146
06.07.26 16:31 Joseph Weigl

Invest wisely and stay cautious. Don't be influenced by promises of unusually high returns or convincing sales pitches from brokers. I learned this the hard way after falling victim to an investment scam that promised huge profits. Fortunately, I acted quickly and reported the incident to a recovery firm for assistance. Contact: Email: [email protected] Telegram: @Resqprofirm WhatsApp: +1 985 296 9146
06.07.26 16:33 Jaran Løvlien

A heartfelt thank you to RESQPRO FIRM for their commitment and professionalism throughout the investigation of my case. Their team worked diligently and helped recover assets valued at $88,000, which were returned to my wallet. I truly appreciate their support, clear communication, and dedication, and I'm grateful for the assistance I received. Contact: Email: [email protected] Telegram: @Resqprofirm WhatsApp: +1 985 296 9146
07.07.26 18:00 robertalfred175

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07.07.26 18:01 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
09.07.26 19:06 Toivo Walli

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09.07.26 19:10 Misty Alexander

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13.07.26 23:49 [email protected]

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15.07.26 11:53 Sarah Green

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16.07.26 21:38 patricialovick86

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16.07.26 21:38 patricialovick86

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17.07.26 19:24 laimqq90

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17.07.26 20:12 martinsjude080

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18.07.26 17:12 Malthe Larsen

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18.07.26 17:42 پریا رضایی

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18.07.26 17:46 Adem Akışık

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18.07.26 23:51 bernalzenaida

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19.07.26 04:10 Fraddy Pual

I can't thank Fundsretriever enough for everything they did for me. My name is Vanessa Conway, and I'm here to tell you my story of how I recovered money I never thought I'd see again. A few months ago, I put a significant amount of money into what looked like a genuine online investment company. At first, it felt real—they showed me fake profits and convinced me to invest even more. But when I tried to cash out, they went quiet and started asking for extra fees. That's when it hit me—I had been scammed. I was heartbroken, frustrated, and didn't know where to turn. That money was my savings—months of hard work gone. Then I found Fundsretriever online. I reached out, hoping for a miracle. Right away, their team made me feel heard. They were responsive, knowledgeable, and walked me through everything. They didn't just take my case—they took it seriously and kept me in the loop every step of the way. I finally felt like I had real experts fighting for me. And guess what? They actually got my money back. It wasn't instant, and it took teamwork, but it happened. When I saw those funds returned, I cried with joy. I'm sharing this so that anyone else out there who's been scammed knows—don't lose hope. Do your research before investing, and stay far away from platforms that promise too much too fast. And if you've already been stung, don't wait—get professional help immediately. Thank you, Fundsretriever, from the bottom of my heart. You didn't just recover my money—you restored my faith. — Vanessa Conway 📧 [email protected] 📱 WhatsApp: +16035121448 💬 Telegram: @Fundsretriever
19.07.26 19:53 kimberlyhebertt6877

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19.07.26 19:53 kimberlyhebertt6877

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
19.07.26 19:54 kimberlyhebertt6877

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