Science — 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 20 August 2026 and assigned it the closest of 31 fixed categories, at 73% 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.
Growth
60 measurements spanning 92 days, net +1,013. 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 21,064–22,381 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 60
Measured (UTC)
Subscribers
Change
5 Nov 2026, 12:36
22,229
+18
4 Nov 2026, 09:54
22,211
+10
3 Nov 2026, 06:56
22,201
+2
2 Nov 2026, 09:56
22,199
+6
1 Nov 2026, 07:09
22,193
+22
31 Oct 2026, 06:51
22,171
+18
30 Oct 2026, 06:47
22,153
+13
29 Oct 2026, 04:21
22,140
+14
28 Oct 2026, 02:27
22,126
+15
26 Oct 2026, 23:55
22,111
-1
26 Oct 2026, 01:30
22,112
+6
25 Oct 2026, 02:26
22,106
+16
24 Oct 2026, 02:54
22,090
+6
22 Oct 2026, 23:38
22,084
+15
21 Oct 2026, 20:01
22,069
+11
20 Oct 2026, 14:38
22,058
+1
19 Oct 2026, 16:46
22,057
+6
18 Oct 2026, 13:15
22,051
+13
17 Oct 2026, 12:38
22,038
+15
16 Oct 2026, 13:54
22,023
first reading
Engagement
158 posts held, back to 29 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 75 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
7.85%
avg views ÷ 22,229 subscribers
Avg views / post
1,750
39 posts measured
Reaction rate
1.25%
reactions ÷ views · ER floor
Posts in window
39
of 158 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 5 November 2026
Posts held
158 (29 July 2026 – 5 November 2026)
Views total
68,083
Reactions total
849
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
5 Nov 2026, 14:34 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
≈4,080
Videos
≈32
Links
≈3,850
Lifetime counters from Telegram’s own channel header, read 5 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
34m 45s
Average length
3m 29s
Measured directly from 10 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
3,155 reactions across 149 posts, in 14 distinct kinds. The most used accounts for 33.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,060
33.6%
🔥
902
28.6%
👍
819
26.0%
👏
81
2.57%
😢
81
2.57%
🙏
53
1.68%
⚡
37
1.17%
😁
36
1.14%
😱
36
1.14%
🤣
17
0.539%
👎
15
0.475%
🐳
9
0.285%
🤩
5
0.158%
💯
4
0.127%
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 158 of the 158 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 3,333 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 158 most recent posts we hold, published 29 July 2026 to 5 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.
Telegram Stars
Stars received
8
across the posts below
Posts paid on
7
of 158 we hold a reading for · 4%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @postnauka. 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 158 most recent posts we hold for this entry, published 29 July 2026 to 5 November 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
Telegram’s own ‘edited’ marker: 2 of 39 posts held from the last 30 days (5.13%) 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).
Почему верный ответ студента вторичен?
Раньше студент решал задачу час, а с нейросетью стал справляться за пять минут. Есть соблазн назвать это прогрессом, но Ульяна Раведовская предупреждает: скорость сама по себе ничего не доказывает — важно, что за ней стоит. Столкнувшись со сложной задачей, к которой не знаешь, как подступиться, человек склонен целиком делегировать её ИИ-агенту: он получает ответ от нейросети и …
Углерод — основной элемент органической материи. В атмосфере он существует в виде CO₂ и CH₄, концентрация которых напрямую влияет на температуру планеты. В болотных экосистемах углекислый газ из атмосферы переводится в органическое вещество — биомассу и торф. Торфяники, сформировавшиеся в результате этого процесса, накапливают углерод на протяжении тысяч лет.
При торфяном пожаре огромный объем накопленного углерода …
Это правда.
Если у человека возник такой стресс, ему может помочь всё, что вызывает положительные эмоции. А еда — надёжный источник позитива. Кусок мяса или шоколада вас никогда не обманет.
На уровне нервных клеток еда способствует выделению медиаторов положительных эмоций. Как только в ротовой области появляются приятные вкусовые ощущения, а в желудок начинает что-то падать, в мозге начинают секретироваться эндорф…
Ответ: Врач проверяет работу вашего мозжечка.
Мозжечок делает сгибание и разгибание рук и ног более плавными, не слишком резкими. Если мозжечок поврежден, то контроль над силой сгибательных движений утрачивается. Когда мы из положения вытянутой руки пытаемся коснуться кончика носа, то руку сгибаем в локте. При нарушении работы мозжечка мы не сможем плавно коснуться кончика носа, а с большой долей вероятности нажмем …
Как из неорганики появилась органика, а из простых молекул — первые системы, способные воспроизводить самих себя? Где в этой цепочке заканчивается химия и начинается жизнь?
https://youtu.be/XaUHuIckJMk
В новом выпуске «Мыслить как ученый» вместе с биофизиком и эволюционным биологом Арменом Мулкиджаняном разбираем происхождение жизни по этапам: от простейших органических соединений и нуклеотидов к РНК-миру и первым …
Взрослый человек зачастую может решать задачу «9 точек» в течение 10–15 минут. Причина в том, что восприятие задачи незаметно задаёт рамки для решения: мы заключаем себя внутрь квадрата, который визуально собирается мозгом, и не можем представить себе способ вывести линию за пределы стартовой фигуры.
Психологи описывают решение задачи как процесс переструктурирования репрезентации — изменения внутреннего представлен…
Врач проверяет коленный рефлекс.
Так как рефлекс — простая реакция со стороны нервной системы, по ней можно проверить работу того или иного отдела ЦНС.
Коленный рефлекс управляется нижними сегментами спинного мозга. Если они повреждены, коленный рефлекс будет выражен чрезмерно сильно. Существуют и другие рефлексы, которые можно запустить, ударяя молоточком по сухожилиям других мышц, например по сухожилиям в районе …
«Стохастический попугай» — один из полюсов дискуссии о генеративном ИИ. На другом полюсе — склонность видеть в модели подобие субъекта.
Показательно, что сам язык описания машинного обучения антропоморфен: модели «поощряют» и «наказывают», им приписывают цели, о них говорят, что они намеренно вводят пользователя в заблуждение, «галлюцинируют» или расставляют приоритеты. Такие формулировки неизбежно возвращают к вопр…
Представьте, что вы выполняете длинную последовательность действий и каждое из них получается правильно с вероятностью 99 %. Одна операция почти всегда проходит успешно, но если таких операций сотни или тысячи, ошибки начинают накапливаться. В результате точность вычислений постепенно падает. В какой-то момент полезного сигнала становится так мало, что результат уже трудно отличить от случайного.
Именно поэтому шумы…
«Для нейтральных частиц такая возможность существует. Например, фотон и Z-бозон являются античастицами самим себе, а другие нейтральные частицы — нет. Для нейтрино вопрос пока открыт. И он связан с двумя разными математическими описаниями: дираковскими и майорановскими нейтрино.
Пока не очень понятно, как на этот вопрос удастся ответить. По сути, главный эксперимент, который мог бы пролить на это свет, — это безнейт…
Бессонница — это не только проблема ночного сна. Это состояние постоянного возбуждения нервной системы, которое, в частности, приводит к трудностям с засыпанием.
Кортизол — гормон, который регулирует углеводный обмен организма и участвует в реакции на стресс. У здорового человека его уровень минимален вечером, ночью он начинает повышаться, а пик приходится на предутренние часы.
У людей с бессонницей выработка корти…
Классический пример — узелок на верёвочке. Вместе со взрослым ребёнок учится создавать знаки и, глядя на узелок, вспоминает, к чему он привязан.
Так же устроено освоение счёта: сначала счётные палочки раскладываются на столе, затем ребёнок представляет их мысленно и наконец оперирует числами как абстракциями.
Всё, что у человека внутри, когда-то было снаружи. Сегодня ситуация меняется: часть интеллектуальных компет…
👍12👏5❤3
Showing the 12 most recent of 158 posts we hold for @postnauka. 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
@postnauka 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
27 August 2026
Most recent edit
27 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 5 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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 23 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
N + 1 @nplusone · 65,343 Telegram ranks this channel #6 of 96 here — alongside 95 others — read 21 August 2026
Наука @naukatv_ru · 23,601 Telegram ranks this channel #13 of 94 here — alongside 93 others — read 18 September 2026
Теории и Практики @tandp_ru · 22,008 Telegram ranks this channel #24 of 100 here — alongside 99 others — read 21 September 2026
Vert Dider @vertdider · 27,106 Telegram ranks this channel #38 of 96 here — alongside 95 others — read 11 September 2026
Вокруг Света | Путешествия • История • Наука @vokrugsveta1861 · 34,288 Telegram ranks this channel #48 of 97 here — alongside 96 others — read 3 September 2026
АНТРОПОГЕНЕЗ.RU @antropogenez_ru · 36,582 Telegram ranks this channel #51 of 97 here — alongside 96 others — read 1 September 2026
Arzamas @ArzamasLive · 59,769 Telegram ranks this channel #52 of 97 here — alongside 96 others — read 22 August 2026
Улица Шкловского - Астрономия и Космонавтика @ShklovskyStr · 19,226 Telegram ranks this channel #62 of 99 here — alongside 98 others — read 3 October 2026
Химия – Просто @ChemistryEasy · 24,885 Telegram ranks this channel #64 of 94 here — alongside 93 others — read 14 September 2026
Критическое мышление @ThinkCritical · 47,031 Telegram ranks this channel #64 of 97 here — alongside 96 others — read 26 August 2026
Физика от Побединского @physfrompobed · 27,223 Telegram ranks this channel #68 of 95 here — alongside 94 others — read 13 September 2026
Доктор Утин @doctorutin · 24,612 Telegram ranks this channel #73 of 97 here — alongside 96 others — read 16 September 2026
Дубынин о мозге 🧠 @dubininvaofficial · 44,754 Telegram ranks this channel #74 of 97 here — alongside 96 others — read 28 August 2026
Fun Science @funscience · 34,231 Telegram ranks this channel #78 of 97 here — alongside 96 others — read 3 September 2026
Популярная механика ⚙️ @Popmeh · 29,484 Telegram ranks this channel #79 of 88 here — alongside 87 others — read 8 September 2026
Всё как у зверей / радио Тимонова @timonova · 20,465 Telegram ranks this channel #90 of 96 here — alongside 95 others — read 27 September 2026
This channel appears in 16 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cross-platform identity — Wikidata
A Wikidata item names this Telegram handle as belonging to the entity it describes. This is Wikidata’s claim, not a verification made by this register — nobody here confirmed that the account is genuinely operated by the entity named. Wikidata content is CC0; every fact below is dated to when it was read from Wikidata, not to when the association was first made there.
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 5 November 2026 — this
entry's latest reading, not the date you are reading this.
“ПостНаука” (@postnauka), 22,229 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/postnauka.
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.