Telegram RegisterThe public register of Telegram

Channel

Авернус

@avernuslab

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · Posts · Citations · Cite this entry

5,339subscribers

-5 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001077282953
TypeChannel
Username@avernuslab
Created20 December 2016measured — cross-checked against a third-party dataset (TGDataset)
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/avernuslab

Topic

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 99% 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 1 other registered channel. 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 (3 of the pairs behind the counts below)
Posted firstThenOverlapGap
@keytosense/192615 Jul 2026, 11:53 UTC@avernuslab/1692 · this entry15 Jul 2026, 11:54 UTC1.00under a minute
@keytosense/193220 Jul 2026, 09:28 UTC@avernuslab/1694 · this entry20 Jul 2026, 09:28 UTC1.00under a minute
@keytosense/193728 Jul 2026, 07:28 UTC@avernuslab/1697 · this entry28 Jul 2026, 07:29 UTC1.00under a minute
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@keytosense15 (8/8 hand-verifiable sample passed)1.00under a minute@keytosense (150)

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 12 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 19 comparable posts for this entry, running 1 July 2026 to 4 August 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 2, the earliest publisher we hold is @keytosense. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_copy, 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 1 other registered channel, 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.

Growth

5,3395,3445,341.56 August 2026 — 5,344 subscribers6 August 2026 — 5,344 subscribers9 August 2026 — 5,341 subscribers12 August 2026 — 5,339 subscribers6 August 202612 August 2026
4 measurements spanning 7 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 5,338–5,345 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 18:175,339-2
9 Aug 2026, 08:415,341-3
6 Aug 2026, 03:365,344no change
6 Aug 2026, 00:325,344first reading

Engagement

21 posts held, back to 1 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 8 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
2.28%
avg views ÷ 5,339 subscribers
Avg views / post
122
12 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
12
of 21 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 11 August 2026
Posts held21 (1 July 202611 August 2026)
Views total1,459
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 04:25 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

Recent posts

11 Aug 2026, 13:14 UTC49 viewsread 12 August 2026
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Почему во все времена люди стремились объединяться в сообщества? Если посмотреть на историю, видна одна устойчивая закономерность. Человеку недостаточно просто находиться в обществе. Ему важно находить своих людей, с которыми совпадают интересы, ценности или представление о будущем. В Англии XIX века существовали сотни джентльменских клубов. Причём рядом с политическими и научными клубами появлялись и весьма экстра

4 Aug 2026, 08:05 UTC96 viewsread 12 August 2026
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Иногда убеждения приходится менять не потому, что вы готовы, а потому, что прежняя картина мира больше не соответствует реальности. Семнадцатилетняя дочь сообщает о беременности. Сын отказывается продолжать семейную военную традицию и решает стать дизайнером. В обоих случаях родители сталкиваются не только с поступком ребёнка. Рушатся их планы и представления о том, какой должна быть правильная жизнь. Дальше есть

3 Aug 2026, 08:23 UTC91 viewsread 12 August 2026

⭐️Внимание. Курс "Коррекция убеждений" стартует завтра Напоминаю, что вас ждет 8 встреч на платформе Zoom продолжительностью 1,5 часа каждая. В процессе обучения Вы научитесь: - помогать людям разрушать ограничивающие и создавать поддерживающие убеждения (либо наоборот!); - менять свои собственные убеждения на более эффективные; - использовать фокусы языка для ответа на упреки, "наезды" и обвинения в ваш адрес; -

31 Jul 2026, 13:10 UTC114 viewsread 12 August 2026

Нам каждый день приходится в чем-то убеждать людей Супруги спорят, на что потратить новогоднюю премию – на шубу или отдых за границей. Бизнес-партнеры обсуждают, стоит ли вкладывать средства фирмы в рисковый проект. Вы пытаетесь донести до начальника, что любите свою работу, но отдавать ей семь дней в неделю физически не в состоянии. И таких примеров множество. Сама жизнь прямо намекает нам: «Хочешь побеждать? Учис

29 Jul 2026, 18:13 UTC121 viewsread 12 August 2026

Сколько существует человечество, столько люди пытаются убедить друг друга в собственной правоте. И далеко не всегда мирными способами. Почему? Потому что нам трудно принять простую мысль: характер и мышление другого человека могут кардинально отличаться от наших собственных. Каждому кажется очевидной именно его картина мира. Она знакома ему столько, сколько он себя помнит. А находиться внутри привычных убеждений п

29 Jul 2026, 13:53 UTC113 viewsread 12 August 2026
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Участницы 19-го потока курса психотипов Юля и Альбина подготовили классную презентацию о том, как 7 радикалов проявляются в живописи. Рекомендую с ней ознакомиться. Она помогает увидеть знакомые психотипы с новой стороны и лучше понять, как характер художника проявляется в его работах.

28 Jul 2026, 07:29 UTC120 viewsread 12 August 2026
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Что делать, если не получается найти выход из конфликта Приходилось ли вам сталкиваться с ситуациями, когда конфликт, на первый взгляд, неразрешим? Например, из-за партнера у вас произошел кассовый разрыв и это привело к крупным штрафам. Или молодожёны пытаются бескомпромиссно «делить» подаренные на свадьбу деньги, разумеется, лучше зная, куда их потратить. Если же приводить примеры неразрешимых конфликтов на рабоч

25 Jul 2026, 15:23 UTC149 viewsread 12 August 2026

Как перестать срываться на провокации Если на вас наезжают, то чаще всего первая реакция - это агрессия в ответ. Это дает манипулятору возможность обвинить вас в неадекватности. Он выставил вам претензию, например назвал вас эгоистом, вы на нее резко ответили. И он подводит итог: "-Ты не только эгоист, но еще и истеричка" Смотрите в чем секрет. Причина ваших эмоциональных реакций внутри вас. Вы же не будете реагиро

22 Jul 2026, 08:37 UTC170 viewsread 12 August 2026
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Почему на курсе «Коррекция убеждений» я использую фокусы языка Можно привести 10 аргументов, и не сдвинуть убеждения человека ни на миллиметр. Потому что убеждения редко держатся только на логике. За ними стоят привычные способы объяснять события. Например, человек говорит: «Если я ошибусь, окружающие перестанут меня уважать». Если начать доказывать, что это неправда, он еще активнее станет защищать свою позицию.

20 Jul 2026, 09:28 UTC138 viewsread 12 August 2026
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Для кого предназначен курс «Коррекция убеждений»? Через две недели стартует новый поток курса. И самый частый вопрос, который мне сейчас задают: «Этот курс вообще для меня?» Отвечу просто. Он для вас, если вы хотя бы раз сталкивались с ситуацией, когда логика переставала работать. Вы приводите аргументы, а человек вас не слышит. Или сами понимаете, что ваши страхи и сомнения сильнее здравого смысла. Разумом знае

15 Jul 2026, 11:54 UTC154 viewsread 12 August 2026
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Нас программируют раньше, чем мы учимся говорить. Ребёнок ещё не способен критически оценивать слова родителей. Он просто принимает их за истину. Так появляются установки, которые спустя годы продолжают влиять на его жизнь. Особенно прочно они закрепляются, если совпадают с ведущим радикалом ребёнка. Представьте девочку с истероидным радикалом, родители которой исполняли каждый её каприз. Какая модель поведения мо

Showing the 12 most recent of 21 posts we hold for @avernuslab. 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.

Citation-graph rank

Citation-graph rank — 764,916 of 1,151,006entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republishes

Channels on the register whose posts this channel has forwarded.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

Named by

Channels on the register whose posts name this channel's handle.

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 12 August 2026 — this entry's latest reading, not the date you are reading this.

“Авернус” (@avernuslab), 5,339 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/avernuslab.

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.