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 the other topics.
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 in near-verbatim form on 1 other registered channel. This entry also sits inside a group of 4 channels linked by matching posts, directly or through other channels in the group; two members of the group may share no posts 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.
No sample pairs were kept for this entry. The counts below were measured, but without the pairs there is nothing here for you to open and check, so treat the relationship as recorded rather than demonstrated.
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
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 159 comparable posts for this entry, running 1 August 2026 to 14 November 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).
Of the group of 4 channels, the one whose matching posts we hold earliest 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
24,200 average views per post against 13,024 subscribers — an engagement rate of 185.7%. Across the 21,335 registered channels in the same cohort — 10,000–31,621 subscribers, posting mainly in Russian — the middle half sit between 5.84% and 23.6%, with a median of 12.1%.
What this was computed from
Window
30 days (6 October 2026 – 5 November 2026)
Posts measured
22 of 22 published in the window (0 exact, 22 rounded by Telegram)
Views totalled
532,190
Mature posts only
172.6% over 17 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 15 November 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.
Channels linked by matching posts
This channel is in a group of 4 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim 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.
64 measurements spanning 100 days, net +3,395. 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 9,274–13,687 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 64
Measured (UTC)
Subscribers
Change
13 Nov 2026, 21:59
13,178
+55
11 Nov 2026, 02:12
13,123
+20
9 Nov 2026, 09:07
13,103
+35
7 Nov 2026, 23:51
13,068
+16
6 Nov 2026, 21:05
13,052
+9
6 Nov 2026, 00:19
13,043
+19
5 Nov 2026, 02:39
13,024
+3
4 Nov 2026, 05:51
13,021
+40
3 Nov 2026, 03:01
12,981
+13
2 Nov 2026, 00:44
12,968
+25
1 Nov 2026, 01:50
12,943
+2
31 Oct 2026, 03:25
12,941
+44
30 Oct 2026, 01:11
12,897
+11
29 Oct 2026, 02:48
12,886
+46
28 Oct 2026, 03:57
12,840
+46
27 Oct 2026, 03:51
12,794
+40
26 Oct 2026, 00:46
12,754
+22
25 Oct 2026, 02:09
12,732
-1
24 Oct 2026, 01:58
12,733
+93
23 Oct 2026, 01:59
12,640
first reading
Engagement
161 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 62 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
219.2%
avg views ÷ 13,178 subscribers
Avg views / post
28,900
58 posts measured
Reaction rate
0.445%
reactions ÷ views · ER floor
Posts in window
58
of 161 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 14 November 2026
Posts held
161 (1 August 2026 – 14 November 2026)
Views total
1,675,150
Reactions total
7,462
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
14 Nov 2026, 20:54 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
Photos
≈840
Videos
≈1,270
Links
≈1,250
Lifetime counters from Telegram’s own channel header, read 14 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
1h 08m
Average length
50s
Measured directly from 83 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
18,949 reactions across 155 posts, in 69 distinct kinds. The most used accounts for 28.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
5,355
28.3%
🔥
3,461
18.3%
😁
3,094
16.3%
🤯
852
4.50%
custom 5471910410959495944
793
4.18%
🤡
725
3.83%
💔
617
3.26%
🥰
489
2.58%
👏
422
2.23%
custom 5202033001294243735
316
1.67%
custom 5197567429307313165
294
1.55%
👍
245
1.29%
😱
192
1.01%
😢
176
0.929%
custom 5194980428771012268
171
0.902%
💊
159
0.839%
😭
154
0.813%
🤣
133
0.702%
custom 5195367985144966875
115
0.607%
custom 5199765245677053780
110
0.581%
49 further kinds
1,076
5.68%
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 161 of the 161 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 19,748 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 161 most recent posts we hold, published 1 August 2026 to 14 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 14 of 58 posts held from the last 30 days (24.1%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Две художницы сделали головные уборы в виде Эрмитажа и Ростральных колонн
Злобина Серафима (﹫zlosi) и Lady Olgitta (﹫kislojno) делают головные уборы со знаковыми достопримечательностями Петербурга.
В конце октября художницы представили парный кокошник в виде Эрмитажа, который издалека выглядел как настоящее здание. Теперь — шляпки(?) в виде Ростральных колонн.
Со всем этим богатством девушки снимают шикарные ролик…
В Аргентине четыре собаки и одна кошка станут свидетелями на свадьбе. Всех их пара когда-то спасла с улицы
В аргентинском Чиполлетти в эту субботу пройдет свадьба Луны Сан-Мартин и Габриэля Эрнандеса, на которой свидетелями станут пятеро питомцев пары.
Луна и Габриэль познакомились в 2024 году, и, как пишут местные СМИ, их объединила именно любовь к животным. Теперь вся их большая звериная семья примет участие в св…
В Техасе обеспокоенные местные жители вызвали службу защиты животных после того, как заметили на лужайке аллигатора. Он оказался надувным матрасом для бассейна
В американском городе Шугар-Лэнд (в округе которого распространены аллигаторы) местные жители заметили одного из них, который им показался слегка приболевшим.
Они позвонили в службу защиты животных, и там отправили на дело офицера Перес. Когда она прибыла на…
Оригинальный световой меч Дарта Вейдера продали почти за пять миллионов долларов
Световой меч Дарта Вейдера, который использовался в фильмах «Звездные войны: Империя наносит ответный удар» и «Возвращение джедая», продали на торгах Heritage Auctions.
В частности, именно этот меч держал в руках Дарт Вейдер в сцене с фразой «Я твой отец».
Тем не менее организаторы аукциона не рассчитывали на такую сумму. Они ожидали,…
Американские врачи рассказали о пациенте, который видит в лицах людей черты своей кошки — и наоборот. Это редкий случай прозопаметаморфопсии — расстройства, при котором лица выглядят искаженными
Исследователи впервые описали прозопаметаморфопсию (ПМО) в начале XX века. Это довольно редкое расстройство, чаще всего связанное с травмами мозга, при котором люди видят лица искаженными.
Насколько? Ну, довольно сильно
Ли…
Помните енота, который устроил погром в алкогольном магазине и заснул в туалете? С ним сделали мерч, который помог собрать для приюта 290 тысяч долларов
В декабре прошлого года этот енот устроил налет на алкогольный магазин в американском Ашленде. В ходе своего вторжения он разбил и, вероятно, попробовал 14 бутылок алкоголя, в том числе рома, самогона, водки и нескольких видов виски. После этого он забрался в туалет…
В Детройте две лошади попробовали прокатиться в общественном транспорте. Другим пассажирам и городским властям это не понравилось
Владельца лошадей на этом видео зовут Джордан Уильямс. По его словам, он приехал с ними на благотворительное мероприятие, где катал детей.
Он также рассказал, что это не первый раз, когда он возит лошадей по Детройту в автобусе: «Мы ездили по Джефферсону, по Чалмерсу, по Коннерсу, и вот …
В Беларуси заметили канализационные люки из Мадрида. Теперь интернет-следователи гадают, как они там оказались
В Могилеве обнаружили канализационные люки с надписью «Мэрия Мадрида». Ролик с люками, который выложил местный гид Ярослав, почти одновременно стал популярным и в испанском, и в беларуском сегментах интернета и заставил всех гадать, как это возможно.
Скажем сразу, Могилев далеко не единственный город, в ко…
У берегов Флориды затопили исторический пароход SS United States, чтобы превратить его в искусственный риф
В 1952 году лайнер SS United States считался технологическим чудом. Он был на 33 метра длиннее «Титаника» и в своем первом рейсе через Атлантику установил рекорд средней скорости — 66 км/ч.
Всего за время своего существования SS United States совершил более 800 трансатлантических переходов, а его пассажирами в…
Незрячая итальянка стала пилотом и налетала уже 200 часов
У Лючии Сабрины Папа врожденная дистрофия сетчатки, из-за которой она не видит. Несмотря на это, она с детства мечтает о полетах — с тех пор как вместе с семьей жила недалеко от аэродрома и ежедневно слышала звук самолетов.
Меня притягивал этот мощный рев, который словно хотел оторвать меня от земли. Я постоянно представляла небо — огромное и свободное, в то…
В Индии спасли российского парапланериста, который застрял на высоковольтных проводах и провел так несколько часов
Российский парапланерист Алексей Ивахин повис на электрических проводах на высоте 75 метров в пяти километрах от индийского города Манди.
По словам спасателей, ему повезло, что во время инцидента он соприкоснулся только с одним проводом и это не привело к трагедии.
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В Норвегии используют более двух тысяч подводных роботов, оснащенных ИИ, стереокамерами и лазерами для защиты лосося от паразитов. Этот способ более гуманный, чем другие, но его все равно критикуют
В Норвегии очень много лососевых ферм, и их постоянно атакуют морские вши. Паразиты прикрепляются к рыбам, вызывая у них стресс и ухудшение здоровья.
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custom 547191041095949594433🔥27😢20❤9🤔7
Showing the 12 most recent of 161 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 2 posts 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
5 November 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 32 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 13 November 2026 — this
entry's latest reading, not the date you are reading this.
“43 / Сорок три” (@sorok_tri), 13,178 subscribers as measured 13 November 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.
