Other / unclassifiable — 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 29 September 2026 and assigned it the closest of 31 fixed categories, at 42% 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
4 measurements spanning 51 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 52–54 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
27 Sept 2026, 09:39
52
-1
29 Aug 2026, 10:48
53
-1
10 Aug 2026, 08:46
54
no change
7 Aug 2026, 03:16
54
first reading
Engagement
10 posts held, back to 22 July 2024 — 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 10 posts for this entry, the most recent from 26 May 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
1m 55s
Average length
29s
Measured directly from 4 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
33 reactions across 6 posts, in 6 distinct kinds. The most used accounts for 48.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
16
48.5%
🔥
7
21.2%
❤🔥
5
15.2%
🕊
2
6.06%
🙏
2
6.06%
👍
1
3.03%
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 6 of the 10 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 33 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 10 most recent posts we hold, published 22 July 2024 to 26 May 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.
😝😝😜🥰😝🙂😜
🌱🌱🌱🌱✅🌱🌱🌱🌱
😘же пару лет я провожу всё лето на берегу Ладоги и очень люблю принимать там гостей.
😗а это время там, прямо на берегу, почти у самой воды, сам собой материализовался довольно большой кэмпинг: с моими типи, гамаками, полноценной лесной кухней, баней и даже прекрасной площадкой для йоги и практик с бомбическим видом на Ладогу - закаты там волшебные.
😘 всегда рад видеть там всех, кто найдёт причин…
🏕Ребята, разрешите в этот прекрасный летний день немного рассказать о цели Персей Кемпа. Что же породило нашу команду делать кемпы с музыкой?
Идея возникла случайно. Наш идейный вдохновитель Персей кемпа @zevs_persey Саша сказал: «Коля, смотри, видишь, как люди сближаются? Это клей… клей отношений и дружбы».
Мы собираемся не только ради музыки 🎶, костра 🔥 или танцев под звёздами 🌌.
Главная сила Персей Кемпа— в людях…
😙😘😛🤓😝🥰☺️😋😜😛😘😝😙 ⤵️
😜😛🙂😜😝
🌱🌱🌱🌱❤️🌱🌱🌱🌱
😝орошие новости.
😘 потихоньку раскачал Профилакторий. Гости заезжают на выходных и на неделе, ну а я тут живу уже второй месяц и всему этому я очень рад.
😝озможно это лучшее мое лето за последние лет 10.
🌱🌱🌱🌱❤️🌱🌱🌱🌱
😘☺️🙂😙😝🙂☺️🤨😝😄
🌱🌱🌱🌱💚🌱🌱🌱🌱
🟠АВГУСТ
🤩08-09 - Приезжает 20 человек эковолонтеров - будем убирать берег и лес от мусора.
🟠СЕНТЯБРЬ
🤩18-20 - Церемония Темаскаль (все места на церемонию разобраны, можно приехать сходить в обычную баню и почилить).
🤩26-27 - Праздник урожая (осеннее равноденствие) - просто большой костер в лесу. Нужно побольше народу, чтобы хоровод нормальный поводить.
🌱🌱🌱🌱🌱
😛стальные даты пока свободны.
😛😙😝🙂☺️🤨😝😄
🌱🌱🌱🌱🔅🌱🌱🌱🌱
😋анал посвещен бесплатному лесному оздорвительному кэмпингу на берегу Ладоги.
🌱🌱🌱🌱🌱
😚то прекрасное место у мыса Песоцкий Нос. Там огромный песчаный пляж протяженностью больше 10 км и очень красивый сосновый лес. Место труднодоступное, по сравнению с другими пляжами Ладоги, а значит чуть более тихое и чистое чем остальные.
🤨а одной из полянок этого берега, в лесу установлены типи (индейские виг…
Showing the 10 most recent of 10 posts we hold for @profilactoriy. 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.
Forward network
Republishes
Channels on the register whose posts this channel has forwarded.
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 1 registered channel — 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 27 September 2026 — this
entry's latest reading, not the date you are reading this.
“Типичный Профилакторий” (@profilactoriy), 52 subscribers as measured 27 September 2026. Telegram Register, tgregister.com/channel/profilactoriy.
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.
