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 11 September 2026 and assigned it the closest of 31 fixed categories, at 72% 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
20 measurements spanning 76 days, net +60. 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 8,278–8,357 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
22 Oct 2026, 14:45
8,348
+2
19 Oct 2026, 19:08
8,346
+2
14 Oct 2026, 09:37
8,344
+2
10 Oct 2026, 21:17
8,342
-4
4 Oct 2026, 22:59
8,346
+33
26 Sept 2026, 03:19
8,313
+3
15 Sept 2026, 05:55
8,310
-2
11 Sept 2026, 10:02
8,312
+7
6 Sept 2026, 18:57
8,305
-15
2 Sept 2026, 08:04
8,320
+3
30 Aug 2026, 08:53
8,317
+2
27 Aug 2026, 05:47
8,315
+5
24 Aug 2026, 13:47
8,310
+11
20 Aug 2026, 22:23
8,299
+1
17 Aug 2026, 22:12
8,298
+4
14 Aug 2026, 19:16
8,294
-4
10 Aug 2026, 23:11
8,298
+11
8 Aug 2026, 08:47
8,287
-1
7 Aug 2026, 11:45
8,288
no change
7 Aug 2026, 11:37
8,288
first reading
Engagement
8 posts held, back to 31 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 21 pages 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 8 posts for this entry, the most recent from 17 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
4m 03s
Average length
1m 01s
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
440 reactions across 8 posts, in 6 distinct kinds. The most used accounts for 39.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
173
39.3%
🔥
149
33.9%
👍
66
15.0%
👏
49
11.1%
👎
2
0.455%
😁
1
0.227%
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 8 of the 8 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 440 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 8 most recent posts we hold, published 31 July 2026 to 17 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.
На рынке падела сейчас настоящая битва: за лучшие локации, тренеров, игроков и тд.
Значит, самое время наконец собрать всех, кто сегодня двигает эту индустрию вперёд ⚡️
Приглашаю владельцев падел-клубов со всей страны 15 октября на BUENOS PADEL SUMMIT 2026 🎾
Сначала встретимся на кортах в турнире основателей PRO-AM Challenge - в формате основатель / акционер клуба + тренер. Причём от одной компании можно заявить н…
Екатеринбург — очень близкий для меня город
⠀
Когда-то давно, когда у нас только появилась генетическая лаборатория Medical Genomics и мы начали активно развиваться по стране, то с командой решили открыть офисы не только в Москве и Твери, но и в Екатеринбурге
⠀
Как сейчас помню: приезжал сюда, останавливался в «Высоцком», а наш офис был на улице Мамина-Сибиряка
⠀
И уже тогда Екатеринбург мне очень запомнился
⠀
Я иног…
Самое сложное — дожить до «96-го шага»
Почему в бизнесе ты можешь годами много работать, вкладывать силы, время и деньги — и всё равно не видеть ощутимого результата?
Недавно увидел очень простой график, который четко дает ответ на этот вопрос
На нём две линии:
🔹синяя — когда ты прибавляешь
🔸оранжевая — когда умножаешь
И парадокс в том, что очень долго прибавление выигрывает. Но примерно на 96-м шаге линии встреч…
Сегодня мы официально открыли Клинику Фомина в Ульяновске ❤️
⠀
Но этот пост не столько про новую клинику, сколько про то, как на самом деле выглядит карьерный путь внутри большой компании!
⠀
Мне всегда нравились люди с проактивной позицией — те, кто еще не получил должность, но уже думает как человек, отвечающий за результат
⠀
За эти годы Владимир Чепрасов возглавил Клинику Фомина в Сочи, стал операционным директором…
Чем дольше занимаюсь бизнесом, тем чаще ловлю себя на одной мысли
Большинство компаний продают совсем не то, что нам кажется ⚡️
Мы привыкли смотреть на бизнес глазами клиента ⬇️
✔️Клиника оказывает медицинские услуги
✔️Ветеринарная клиника лечит животных
✔️Падел-клуб продает возможность поиграть
✔️Супермаркет продает продукты
✔️Авиакомпания продает перелеты
Но если посмотреть на эти компании глазами собственника, …
Есть цифры, которые меняют не финансовое положение компании, а мышление команды
Мы долго ждали этого момента.
И даже заранее договорились с советом директоров: как только месячная выручка превысит 1 миллиард рублей, я приглашу всю команду в свою аутентичную баню
Обещание выполнил уже вчера 🤌🏼
Для кого-то миллиард — просто цифра.
Для кого-то — красивый заголовок.
А для меня это прежде всего символ очередного преодо…
29 июля у нас был рекордный день по выручке за всю историю компании — 44 миллиона ₽ за один день
⠀
Конечно, первая эмоция — радость 😍 Можно поздравить команду, сказать, что мы молодцы, зафиксировать красивую цифру и пойти дальше
⠀
Но я всегда говорю себе и своей команде: рекорд — это не просто повод для праздника. Рекорд — это прецедент
⠀
А если что-то случилось один раз, значит, теоретически это может повториться. Г…
🔥39❤24👏8👍5👎2
Showing the 8 most recent of 8 posts we hold for @dr_fomin. 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.
Mentions
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@dr_fomin named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@fominclinic named in 5 posts, 8 August 2026 – 26 August 2026
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.
Юрист для врача Ангелина Романовская @mfcexpert_news · 29,817 Telegram ranks this channel #5 of 96 here — alongside 95 others — read 8 September 2026
Поясни за мед @poyasni_za_med · 22,242 Telegram ranks this channel #16 of 97 here — alongside 96 others — read 21 September 2026
Медицинская Россия @mediamedics · 143,125 Telegram ranks this channel #18 of 95 here — alongside 94 others — read 13 August 2026
MD.school | Медицинский онлайн-университет | Доказательная медицина @medicina_discendi · 21,155 Telegram ranks this channel #24 of 98 here — alongside 97 others — read 25 September 2026
Аккредитация врачей | Ординатура @credit_med · 23,201 Telegram ranks this channel #24 of 96 here — alongside 95 others — read 19 September 2026
ДОКТОР ХАН @doctorkhanstanislav · 57,375 Telegram ranks this channel #24 of 97 here — alongside 96 others — read 23 August 2026
ДОКТОР ВАРНАВСКИЙ @doctor_varnavskiy · 24,897 Telegram ranks this channel #25 of 82 here — alongside 81 others — read 13 September 2026
Нефролог I Данила Пыриков @pyrikov · 67,207 Telegram ranks this channel #33 of 98 here — alongside 97 others — read 20 August 2026
Соколова наизнанку @naiznankuo · 59,380 Telegram ranks this channel #40 of 95 here — alongside 94 others — read 23 August 2026
Медач | Medical Channel @medach · 28,013 Telegram ranks this channel #44 of 97 here — alongside 96 others — read 10 September 2026
Занимательная эндокринология @funwithmedicine · 22,731 Telegram ranks this channel #52 of 98 here — alongside 97 others — read 20 September 2026
dnevnikdoctora @dnevnikdoctora · 45,172 Telegram ranks this channel #52 of 98 here — alongside 97 others — read 27 August 2026
Газовый гигант (ibs.doc)🪐 @ibs_doc · 21,701 Telegram ranks this channel #65 of 100 here — alongside 99 others — read 23 September 2026
Доктор Лесков @doctorleskov · 27,795 Telegram ranks this channel #67 of 92 here — alongside 91 others — read 10 September 2026
This channel appears in 14 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 22 October 2026 — this
entry's latest reading, not the date you are reading this.
“ДОФ⭕️МИН | Дмитрий Фомин” (@dr_fomin), 8,348 subscribers as measured 22 October 2026. Telegram Register, tgregister.com/channel/dr_fomin.
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.