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Channel

Научпоп

@flibri

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

7,280subscribers

+9 since we began measuring on 5 August 2026

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

Register entry

Telegram ID-1001139355531
TypeChannel
Username@flibri
Created31 May 2017measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live24 August 2026
Measurements held6
Confirmed unchanged1 time, most recently 24 August 2026
On Telegramt.me/flibri

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

7,2687,2807,2745 August 2026 — 7,271 subscribers6 August 2026 — 7,271 subscribers11 August 2026 — 7,268 subscribers15 August 2026 — 7,275 subscribers18 August 2026 — 7,277 subscribers24 August 2026 — 7,280 subscribers5 August 202624 August 2026
6 measurements spanning 19 days, net +9. 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 7,266–7,282 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
24 Aug 2026, 23:257,280+3
18 Aug 2026, 06:327,277+2
15 Aug 2026, 07:187,275+7
11 Aug 2026, 16:277,268-3
6 Aug 2026, 03:077,271no change
5 Aug 2026, 22:067,271first reading

Engagement

25 posts held, back to 18 February 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 14 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
14.4%
avg views ÷ 7,280 subscribers
Avg views / post
1,050
7 posts measured
Reaction rate
0%
reactions ÷ views · ER floor
Posts in window
7
of 25 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 15 August 2026
Posts held25 (18 February 202615 August 2026)
Views total7,341
Reactions total0
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken20 Aug 2026, 11:48 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.

Telegram Stars

Stars received
27
across the posts below
Posts paid on
20
of 24 we hold a reading for · 83%
Most on one post
3
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @flibri. 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 25 most recent posts we hold for this entry, published 18 February 2026 to 15 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.

Recent posts

1 Aug 2026, 11:48 UTC≈1,390 views0 reactions1 Starread 20 August 2026
Photo

О годичных кольцах и пыльце. Истории о прошлом человечества глазами растений — Денис Новиков #NewScience Книга показывает, как ботаника помогает реконструировать исторические события. Автор опирается на дендрохронологию и палинологию. Письменные источники субъективны или часто теряются, тогда как растения постоянно фиксируют объективные данные о климате, природных катастрофах и миграциях. Издание решает проблему н

13 Jul 2026, 21:31 UTC≈2,140 views0 reactions1 Starread 20 August 2026
Photo

Математика для тех, кто боится математики — Бен Орлин Книга решает одну главную задачу: помогает взрослым людям избавиться от школьных травм, связанных с точными науками. В обществе принято условно делить людей на технарей и гуманитариев. Из-за этого многие годами живут с убеждением, что цифры, уравнения и графики недоступны для их понимания. Автор доказывает обратное и показывает, что математика требует не врожденн

8 Jul 2026, 07:08 UTC≈2,150 views0 reactions1 Starread 20 August 2026
Photo

Если кто-то его создаст – все погибнут. Почему сверхчеловеческий ИИ уничтожит нас всех — Элиезер Юдковский, Нейт Соарес Исследователи машинного интеллекта Элиезер Юдковский и Нейт Соарес объясняют логические причины риска создания искусственного сверхразума. Авторы доказывают простую мысль: появление алгоритма, превосходящего человека по когнитивным способностям, приведет к гибели человечества. Причина кроется в тех

29 Jun 2026, 17:15 UTC≈2,060 views0 reactions2 Starsread 20 August 2026
Photo

Как животные: что интимная жизнь насекомых, птиц и зверей говорит нам об эволюции, биоразнообразии и нас самих — Менно Схилтхёйзен Эволюционный биолог Менно Схилтхёйзен написал книгу о происхождении видов, взяв за основу анатомию и поведение животных в период размножения. Автор рассматривает репродуктивные органы насекомых, птиц и млекопитающих как главный двигатель эволюционных изменений. Согласно тексту, половой о

25 Jun 2026, 08:45 UTC≈2,100 views0 reactions2 Starsread 20 August 2026
Photo

Всё, что движется. Прогулки по беспокойной Вселенной от космических орбит до квантовых полей — Алексей Семихатов Книга физика и популяризатора науки Алексея Семихатова — это масштабное исследование фундаментального свойства нашей Вселенной: движения. Автор показывает, что абсолютно всё вокруг нас, от гигантских галактик до мельчайших элементарных частиц, находится в непрерывном танце, подчиняясь строгим физическим з

20 Jun 2026, 15:12 UTC≈2,110 views0 reactions1 Starread 20 August 2026
Photo

Три склянки пополудни и другие задачи по лингвистике — Коллектив авторов Забудьте о школьной зубрежке правил и скучных диктантах. Лингвистика в этой книге представлена как строгая дисциплина, основанная на поиске закономерностей и логическом анализе. Книга дает мозгу качественную аналитическую нагрузку. Вместо абстрактных теорий авторы предлагают фрагменты на совершенно незнакомых языках. Это могут быть числительны

Showing the 12 most recent of 25 posts we hold for @flibri. 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 — 394,638 of 1,603,893entries 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 3 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.

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

“Научпоп” (@flibri), 7,280 subscribers as measured 24 August 2026. Telegram Register, tgregister.com/channel/flibri.

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.