Health & wellness — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 26 September 2026 and assigned it the closest of 31 fixed categories, at 95% 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.
Growth
6 measurements spanning 55 days, net -2. 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 135–138 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
1 Oct 2026, 14:00
135
-1
17 Sept 2026, 00:18
136
-1
8 Sept 2026, 02:57
137
-1
23 Aug 2026, 04:38
138
+1
8 Aug 2026, 23:16
137
no change
7 Aug 2026, 18:03
137
first reading
Engagement
15 posts held, back to 4 March 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 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 15 posts for this entry, the most recent from 2 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
16m 27s
Average length
2m 03s
Measured directly from 8 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
108 reactions across 12 posts, in 9 distinct kinds. The most used accounts for 37.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
40
37.0%
🔥
34
31.5%
👏
11
10.2%
😍
7
6.48%
😱
7
6.48%
🤣
5
4.63%
😎
2
1.85%
🎉
1
0.926%
🤩
1
0.926%
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 12 of the 15 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 108 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 15 most recent posts we hold, published 4 March 2026 to 2 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.
Абсолютный хит среди шорстов из интервью с профессором-молекулярным биологом.
В этом Shorts — только маленькая часть большого разговора.
В полном интервью разбираем:
🧬 Как на самом деле появился ковид: природа или лаборатория?
🧬 Можно ли менять «сценарии» нашего организма через эпигенетику?
🧬 Реально ли редактирование ДНК?
🧬 Насколько близка наука к созданию вакцины от рака?
🧬 Как молитва влияет на мозг с точки зре…
Всполыхнули любители оземпика, разогнав просмотры рилса своими комментариями.
Просили ссылки.
Прикладываем.
☝️В последних исследованиях уже опровергли риск рака.
Но я бы уж не доверяла на 100% безопасности
на момент записи интервью - исследования по ассоциации применения агонистов рецепторов GLP-1 и медуллярного рака щитовидной железы были в стадии проведения. В них были выявлены повышенные онкологические риски, в …
The shares total 114%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.
Друзья, я рада, что канал несет важное дело - просвещение! Такие интервью с непубличными профессорами, как Марина, - это золотой фонд. Давайте дадим алгоритмам "распробовать" этот глубокий материал, оставив комментарий под видео, если вы его уже посмотрели.
Для тех, кто еще не смотрел, чтобы вам было удобнее ориентироваться в темах, составила для вас навигацию:Таймкоды:
0:00 — О чём этот выпуск: анонс и гость — проф…
1. Эксклюзивный фрагмент, который не вошел в интервью!
Рекомендации молекулярного биолога:
как голодание влияет на организм, кому противопоказано и может ли стать эликсиром молодости.
2. А ТАКЖЕ 🎁 ОБЕЩАННЫЕ МАТЕРИАЛЫ ОТ МАРИНЫ ГРАНОВСКОЙ
📚 Статьи про коронавирус для глубокого изучения:
Происхождение коронавируса: как объединяются вирусы — анализ генома и важные выводы.
Научный разбор механизмов воздействия
Исслед…
Вирус «из пробирки», органы на заказ и конец эпохи рака: мы уже в сериале "Черное зеркало"?
Сегодня у меня в гостях молекулярный биолог, профессор Марина Грановская. Мы сорвали маски с современной медицины и обсудили то, о чем обычно говорят только в закрытых лабораториях:
— Лабораторная утечка: случайность или закономерность? Как работает «обратная генетика» вирусов. Страшная правда про ковид.
— РНК-революция: как…
Завтра! Правда ли, что COVID-19 был сконструирован в лаборатории еще в 2015 году? И если мы научились создавать вирусы, сможем ли мы так же легко «отключать» болезни и старение?
Вирусы «из пробирки», органы на 3D-принтере и конец эпохи рака
🔥 - ждем
Новая реальность с 00:38 сек 😭
Подписывайтесь:
YouTube-канал
Сообщество ВК
Rutube-канал
Страница в Inst
Телеграм-канал
🤣5❤2
Showing the 12 most recent of 15 posts we hold for @obozhe_tg. 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.
Polls
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
The shares total 114%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 15 most recent posts we hold, published 4 March 2026 to 2 August 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
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 1 October 2026 — this
entry's latest reading, not the date you are reading this.
“О Боже, какие люди” (@obozhe_tg), 135 subscribers as measured 1 October 2026. Telegram Register, tgregister.com/channel/obozhe_tg.
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.