Personal blog — 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 94% 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 (5 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 20 comparable posts for this entry, running 17 July 2026 to 6 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 @gryazinbazar — which is this entry. 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 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.
5 measurements spanning 7 days, net -24. 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 6,259–6,291 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 00:15
6,263
-13
9 Aug 2026, 18:42
6,276
-10
7 Aug 2026, 00:38
6,286
-1
6 Aug 2026, 03:21
6,287
no change
6 Aug 2026, 01:32
6,287
first reading
Engagement
31 posts held, back to 17 July 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 9 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
26.8%
avg views ÷ 6,263 subscribers
Avg views / post
1,680
31 posts measured
Reaction rate
1.96%
reactions ÷ views · ER floor
Posts in window
31
of 31 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 11 August 2026
Posts held
31 (17 July 2026 – 11 August 2026)
Views total
51,970
Reactions total
1,020
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 03:21 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.
Reaction mix
936 reactions across 27 posts, in 8 distinct kinds. The most used accounts for 39.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
369
39.4%
👍
179
19.1%
😁
167
17.8%
🐳
122
13.0%
🤡
78
8.33%
💅
12
1.28%
😱
6
0.641%
😢
3
0.321%
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 31 of the 31 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 1,020reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 31 most recent posts we hold, published 17 July 2026 to 11 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.
Telegram Stars
Stars received
499
across the posts below
Posts paid on
27
of 31 we hold a reading for · 87%
Most on one post
83
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @gryazinbazar. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 31 most recent posts we hold for this entry, published 17 July 2026 to 11 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Немного про перподрочку
Какая история была у меня - про Variational и Extended писал еще в начале года. Но я не крутил их в классическом смысле "сделай 100 акков и дельта-нейтраль". Я просто тупо торговал на Ethereal, Variational и Extended.
Получалось даже неплохо, но я решил сильно сократить и уйти в контент. Совсем чуть-чуть продолжал крутить их в дельте.
Сейчас контент-завод +- настроил и снова немного буду то…
Чему меня научил крипто рынок? (часть III)
Мы все слышим эту фразу, да? Ну эту вот "умные тупо думают, а дураки тупо делают - поэтому умные нищие, а дураки богатые".
Кто эту фразу придумал? Какой долбаеб? А интернет начал ее повторять.
Да, бесконечно думать и нихуя не делать - полное говно.
Но дохуя делать тоже не всегда выигрышная стратегия.
Потому сегодняшний урок звучит так - Делать только то, что надо делать…
Медитация на финансовое благополучие
Я знаю, что у многих сейчас проблемы с денежными потоками.
Друзья. Мы можем это исправить. Мы можем вызвать дождь изобилия в вашей жизни!
Для этого я записал медитацию. Уделите ей буквально 5 минут. Вы станете спокойнее, мудрее и богаче после прослушивания.
А чтобы денежные потоки текли еще лучше - пользуйтесь обменником Hermes.
Я чуть не сдох
Но я жив. И да, я записался на каратэ и только что вышел с первого занятия, точнее выполз, но обо всем по порядку.
В школьной юности я ходил на бокс и спарринговался с фанатами футбольных клубов, потому что… потому что "надо".
Ну я же не лох, все мальчики должны уметь драться - и я дрался. Далеко не всегда удачно, но дрался - плюс на улицах родного города было небезопасно, это сейчас я могу ходить с…
Что там по Multipli
Олды на месте? Для дегенов-олдов пост.
Многие мои подписчики закидывали в этот проект еще в 2025 году, вот у них намечается сейл, я чуть опоздал, но не критично.
Освежим память:
Multipli – RWA-уилд протокол. В него занесли Пантера Капитал, что очень неплохо, хоть и был фад на фаундера.
Че щас происходит:
- Идет регистрация на сейл через Sonar до 14 августа, надо пройти KYC. Инфы маловато, го…
Сколько вещей ты потерял, потому что хотел все и сразу?
Месяц походил к логопеду. И нет, это пост не про него, а про твою жизнь. Короч.
Раньше, когда я играл в театре любительском, я тоже занимался речью - но занимался я всем сразу:
- буквой "Р"
- ставил голос
- еще и развивал речь в целом
У меня уходил где-то час в день на это. По итогу я забил. Преподша мне говорила - "занимайся понемногу, но каждый день", а я …
Я тоже зумер
Недавно я пошел на свидание с очень симпатичной зумершей, ей 23 года. (если вы симпатичная зумерша - пишите в ЛС).
Так вот.
Полсвидания она рассказывала мне про университет и диплом, я начал рассказывал ей в ответ свои универские истории - она слушала и сказала, что я по духу тоже зумер.
Я рассказал историю, как я в 22 года работал в одном офисе в мск, а затем в пятницу ушел пиво пить и не вернулся, …
Чему меня научил крипто рынок? (часть II)
Это очень важный пост для каждого из вас. И не надо говорить, что он не про тебя, я тебя через экран вижу, сладкий пупсик, ты очень красивый - но я вижу, что у тебя тоже есть эта проблема.
Итак, IV (четвертый) урок из серии чему меня научил крипто рынок:
Не угадывай. Проверяй.
Смотрите. Это работает везде, но именно в крипте было видно отчетливо.
Мы инвестировали скажем …
Просто представь
С бабками все стало лучше. Ты идешь по улице, весь такой красивый, и тут к тебе подходит шикарная женщина - она хочет познакомиться с тобой.
Ты мнешься, потому что ты не такой, но потом сдаешься и начинаешь давать ей свой Telegram, как вдруг...
ТВОЙ VPN НЕ РАБОТАЕТ :(
Ты не можешь зайти в Телегу! Ведь недавно РКН вьебал кучу ВПН-сервисов. Что делать? Плакать? Нет! Пользуйся ГИГАвпн:
- Работал, д…
Чему меня научил крипто рынок?
Выше я чуток прогрел вас кружком про 2021, чтобы кольнуть в старую боль :) А теперь давайте раз уж мы пошли ностальгировать, я поделюсь тем, чему меня научил крипто рынок.
Сейчас модно (как и на любой медвежке) плеваться в крипту и называть ее говном. В целом, где-то это правда, но опыт, что она дала мне - стоит дороже любых денег.
Итак, чему меня научил САМЫЙ пиздатый год в крипте, …
❤35👍5🐳4🤡1
Showing the 12 most recent of 31 posts we hold for @gryazinbazar. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Citation-graph rank
Citation-graph rank — 39,760 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
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 18 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.
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 August 2026 — this
entry's latest reading, not the date you are reading this.
“Грязный Базар” (@gryazinbazar), 6,263 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/gryazinbazar.
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.
