Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 85% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear word for word on 7 other registered channels. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (6 of the pairs behind the counts below)
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 14 comparable posts for this entry, running 3 September 2025 to 9 July 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Across the whole group of 8, the earliest publisher we hold is @zapusk4. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, last confirmed 7 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 7 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
5 measurements spanning 8 days, net -5. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 2,212–2,219 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
15 Aug 2026, 12:38
2,213
-2
11 Aug 2026, 15:51
2,215
-2
8 Aug 2026, 12:37
2,217
-1
7 Aug 2026, 14:46
2,218
no change
7 Aug 2026, 14:36
2,218
first reading
Engagement
17 posts held, back to 16 August 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 17 posts for this entry, the most recent from 9 July 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
35s
Average length
18s
Measured directly from 2 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
181 reactions across 16 posts, in 5 distinct kinds. The most used accounts for 66.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
121
66.9%
🔥
41
22.7%
❤🔥
12
6.63%
👏
5
2.76%
🤣
2
1.10%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 16 of the 17 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 181reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 17 most recent posts we hold, published 16 August 2025 to 9 July 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Продажи второго сезона вебинаров по ИИ открыты! 🥳
Что изменилось в мире нейросетей за последний квартал? Обсудим это на новых эфирах.
После этих вебинаров вы начнете использовать ИИ на продвинутом уровне (даже если сейчас знания на нуле) и войдете в 5% самых подкованных пользователей мира. У вас будут самые актуальные способы работы с нейросетями на июль 2026 года. Готовьтесь: скоро знакомые начнут обращаться к вам…
С какими целями приходят на интенсив по вайбкодингу?
Собрали несколько историй участников, которые только вчера пришли в ЛАБС:
▪️Татьяна — режиссер-документалист с 1,6 млн подписчиков на YouTube. Хочет приложение для своего проекта про народы России
▪️Диля — владелица онлайн-школы. Хочет свою CRM для работы с учениками, чтобы уйти с дорогой платформы
▪️Анна — продюсер телеграм-канала Павла Гительмана. Хочет дашборд…
Я сегодня завайбкодила приложение для создания медитаций 🔥 чтобы каждый практик, мог сам записать свою медитацию ..даже телесуфлер есть, чтобы было откуда читать ...я пищююю 🥳
Узнайте сейчас, что сможете завайбкодить в ЛАБС 💅
Специально для вас сделали сайт, где вы выбираете свою нишу и роль, а мы придумываем, как повысить вашу ценность для клиентов и добиться ВАУ эффекта в продуктах.
УЗНАТЬ МОЖНО ЗДЕСЬ
ОСТОРОЖНО! Слишком гениально🔥😅
«Мне за эту разработку такууууую премию дадут!»
Друзья, ребята, коллеги — представляем вам обзор на свежеиспеченную 🍞 платформу ЛАБС. Платформу, где прямо сейчас учатся 550+ участников и все работает ЗА-МЕ-ЧА-ТЕЛЬ-НО🤌
А самое главное, что Мари завайбкодила ее сама.
🩶Раньше: плати миллион, жди полгода, ругайся с разработчиками
🩷Сейчас: вы сами можете сделать сервис, где клиенты покупают, смотрят уроки, задают вопро…
Мари, как повезло твоей подруге быть твоей подругой ❤️❤️
Я тоже мама ребёнка с РАС и знания, которые я получила от тебя - изменили мою жизнь. Я создала свою онлайн школу и помогла многим мамам. Этот этап сейчас закрыт..
А я жду вайбкодинга. Давно моё сердце не билось так часто от предвкушения обучения. С масштаба 5, наверное )))
Что для меня вайбкодинг?
Сыну моей подруги диагностировали РАС (расстройство аутистического спектра). Когда я показала ей вайбкодинг — она загорелась идеей сделать сервис для мам детей с аутизмом.
Чтобы к диагнозу относились не как к болезни, а как к особенности. Чтобы мамы могли понимать своих деток.
Она расплакалась, когда осознала, что такие сложные и важные вещи теперь реально создать своими руками.
Подробнее о…
16 декабря в 16:00 мск открываю продажи на второй поток ЛАБС 💖
ЛАБС — это мой интенсив по вайбкодингу. 3 недели люди без технического образования создавали сайты и сервисы, о которых мечтали ГО-ДА-МИ 🤌
Без программистов, без дизайнеров и без стресса (главным правилом было — делать все играючи, мы даже приходили в коронах на эфир 👑)
Участники ЛАБС не только сделали себе сервисы, которых им так не хватало в бизнесе …
Станьте спикером в продуктах Мари✨
Если у вас есть серьезные результаты и вам важно работать в окружении сильных профессионалов — приглашаем вас в число экспертов наших курсов.
Почему стоит стать спикером:
• Вы расширите свою известность и представите вашу экспертизу широкой аудитории.
• Поможете коллегам и ученикам из образовательного сообщества — ваш опыт реально ценен!
• Получите поддержку при записи.
• Вас уви…
Все, что нужно знать о вайбкодинге 💗
6 ноября в 19:00 мск Мари проведет открытый бесплатный вебинар, на котором расскажет:
📍Что такое вайбкодинг
📍Как на этом зарабатывать, а как лучше не стоит))
📍Реальные проекты участников выезда в Армении
📍Ответы на ваши вопросы
Региструйтесь сейчас, чтобы не упустить навык, который уже через год станет стандартом для всех.
▫️ИДУ ВАЙБКОДИТЬ С МАРИ
❤10
Showing the 12 most recent of 17 posts we hold for @dom_deneg_mari. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Mentions
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 15 August 2026 — this
entry's latest reading, not the date you are reading this.
“Дом Денег” (@dom_deneg_mari), 2,213 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/dom_deneg_mari.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.