Memes & entertainment — 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 10 August 2026 and assigned it the closest of 31 fixed categories, at 83% 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. They sit inside a group of 3 channels that share the same post bodies with each other. 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 (2 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 23 comparable posts for this entry, running 1 August 2026 to 7 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 3, the earliest publisher we hold is @sorok_tri — which is this entry. That is a statement about our reading window, not a claim of authorship.
Views per post sit far above this size band
27,100 average views per post against 11,599 subscribers — an engagement rate of 233.9%. Across the 17,892 registered channels in the same cohort — 10,000–31,614 subscribers, posting mainly in Russian — the middle half sit between 4.79% and 17.8%, with a median of 9.22%.
What this was computed from
Window
30 days (23 August 2026 – 22 September 2026)
Posts measured
24 of 24 published in the window (0 exact, 24 rounded by Telegram)
Views totalled
651,040
Mature posts only
242.9% over 22 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal. A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the keys clone_source · err_high, last confirmed 22 September 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 2 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.
32 measurements spanning 45 days, net +1,816. 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 9,511–11,871 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)
Subscribers
Change
19 Sept 2026, 15:40
11,599
+56
17 Sept 2026, 00:58
11,543
+15
15 Sept 2026, 03:01
11,528
+13
13 Sept 2026, 11:37
11,515
+25
11 Sept 2026, 16:21
11,490
+224
9 Sept 2026, 02:17
11,266
+279
5 Sept 2026, 19:21
10,987
+161
3 Sept 2026, 20:37
10,826
+172
2 Sept 2026, 09:48
10,654
+77
1 Sept 2026, 08:15
10,577
+18
31 Aug 2026, 10:14
10,559
+10
30 Aug 2026, 11:45
10,549
+27
29 Aug 2026, 09:12
10,522
+42
28 Aug 2026, 08:54
10,480
+25
27 Aug 2026, 11:23
10,455
+37
26 Aug 2026, 11:04
10,418
+16
25 Aug 2026, 10:04
10,402
+8
24 Aug 2026, 11:13
10,394
+36
22 Aug 2026, 20:16
10,358
+39
21 Aug 2026, 13:26
10,319
first reading
Engagement
103 posts held, back to 1 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 38 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
233.9%
avg views ÷ 11,599 subscribers
Avg views / post
27,100
24 posts measured
Reaction rate
0.389%
reactions ÷ views · ER floor
Posts in window
24
of 103 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
Window
Rolling 30 days · latest post in window 29 August 2026
Posts held
103 (1 August 2026 – 29 August 2026)
Views total
651,040
Reactions total
2,530
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
29 Aug 2026, 14:45 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.
What this channel posts
Video runtime
36m 53s
Average length
46s
Measured directly from 48 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
11,487 reactions across 97 posts, in 62 distinct kinds. The most used accounts for 26.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
3,082
26.8%
😁
2,153
18.7%
🔥
1,840
16.0%
🤡
725
6.31%
🤯
467
4.07%
custom 5197567429307313165
294
2.56%
custom 5471910410959495944
279
2.43%
💔
278
2.42%
👍
245
2.13%
🥰
243
2.12%
👏
229
1.99%
custom 5202033001294243735
213
1.85%
custom 5194980428771012268
171
1.49%
😱
140
1.22%
custom 5195367985144966875
115
1.00%
custom 5199765245677053780
110
0.958%
🤮
75
0.653%
🌚
74
0.644%
🤬
72
0.627%
🥴
70
0.609%
42 further kinds
612
5.33%
Custom emoji. 6 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegram’s.
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 103 of the 103 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 12,286 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 103 most recent posts we hold, published 1 August 2026 to 29 August 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.
Так мог звучать лес юрского периода. Исследователи воссоздали хор звуков, издаваемых древними насекомыми
Ученые проанализировали 20 ископаемых останков насекомых, которые обитали около 165 миллионов лет назад на территории современной Внутренней Монголии.
Благодаря сохранившимся в окаменелостях частям, отвечающим за воспроизведение звуков — например, микроскопическим пилочкам и скребкам на крыльях, которые насекомы…
Сегодня утром в России внезапно перестала открываться Википедия. По этому поводу, во-первых, рассказываем, как к такому подготовиться. А во-вторых, предлагаем сыграть в игру!
Да-да, это реклама! Но она интереснее и полезнее других реклам.
🔷Начнем с первого пункта
Установите бесплатное расширение для браузера «Голос». Оно открывает доступ к независимым СМИ и любым другим заблокированным и «замедленным» сайтам (да, …
Футболист из второй лиги Аргентины посвятил гол одноглазому коту, который долгие годы был талисманом команды
Кот Тату жил на базе «Арсенала Саранди» и был любимчиком игроков, сотрудников клуба и болельщиков.
Особая связь у него была с нападающим Иво Кестлером. Незадолго до последнего матча он зашел в раздевалку и все утро просидел у него на коленях.
Увы, перед игрой с «Итусайнго» Тату умер. Иво очень расстроился и…
В Египте произошло ограбление в стиле «Форсажа». Воры украли 140 килограммов курицы, но все закончилось для них трагично
В соцсетях стало вирусным видео ограбления грузовика, несущегося по трассе. Пользователей соцсетей впечатлили две вещи: то, что целью ограбления стали не деньги или драгоценности, а курица, и то, что все это выглядело как кадры боевика.
На этом веселая часть этой истории заканчивается.
Ограблени…
Шесть психологов, которым уже за 70, дружат более 45 лет благодаря тому, что раз в год собираются поиграть в Dungeons & Dragons. Им не мешают даже споры о политике!
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Попробовать неизвестную игру он позвал нескольких друзей из докторантуры по клинической психологии в Универ…
Немцу продали в пекарне половинку хлеба на 10 граммов меньше, чем должна была быть половинка. Он пожаловался властям. Безумие? Безумие!
Пекарня Breitner's в баварском Пфаффенхофене-на-Ильме существует уже 66 лет. И все эти 66 лет там можно было купить половинку буханки хлеба. Всем все нравилось, и никто не жаловался.
До тех пор, пока в прошлом году один из покупателей не взвесил хлеб дома. Оказалось, что его покупк…
В инстаграме перепись котов-релокантов. Хозяева рассказывают про «карьерный путь» своих питомцев от мусорок до апартаментов Лазурного берега и другой роскошной жизни
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Вчера Билл Гейтс написал эссе объемом почти 6000 слов об опасности ИИ и дал большое интервью The New York Times. Вот что тревожит техномиллиардера
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custom 520203300129424373535❤20😁12🔥5🤣2🤝1
Showing the 12 most recent of 103 posts we hold for @sorok_tri. 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.
Posts edited after publishing
@sorok_tri edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
28 August 2026
Most recent edit
28 August 2026
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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 27 registered channels — 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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 19 September 2026 — this
entry's latest reading, not the date you are reading this.
“43 / Сорок три” (@sorok_tri), 11,599 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/sorok_tri.
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.
