Channel
@dr_zhumanova
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
12,291subscribers
+6 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1001548192338 |
|---|---|
| Type | Channel |
| Username | @dr_zhumanova |
| Description | 👩🏼⚕️Гинеколог Хирург - Руководитель центра гинекологии 🔬Про диагностику и лечение 🌹Интимный эстет - красота и яркость чувств Канал на регистрацию в РКН: https://gosuslugi.ru/snet/69e8bee23918a5e088e5f6e1 |
| Created | Between 1 August 2021 and 31 January 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 12 August 2026 |
| Measurements held | 7 |
| Confirmed unchanged | 1 time, most recently 12 August 2026 |
| On Telegram | t.me/dr_zhumanova |
Health & wellness — 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 10 August 2026 and assigned it the closest of 31 fixed categories, at 100% 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.
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Posts published here appear word for word on 1 other registered channel. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
| Posted first | Then | Overlap | Gap |
|---|---|---|---|
| @drugaya_ginekologiya/111017 Jul 2026, 11:14 UTC | @dr_zhumanova/1371 · this entry22 Jul 2026, 06:01 UTC | 1.00 | 5 days |
| @dr_zhumanova/1370 · this entry21 Jul 2026, 06:03 UTC | @drugaya_ginekologiya/111624 Jul 2026, 05:04 UTC | 1.00 | 3 days |
| @dr_zhumanova/1375 · this entry24 Jul 2026, 14:32 UTC | @drugaya_ginekologiya/111928 Jul 2026, 06:03 UTC | 1.00 | 4 days |
| @dr_zhumanova/1378 · this entry28 Jul 2026, 09:07 UTC | @drugaya_ginekologiya/112130 Jul 2026, 05:04 UTC | 1.00 | 44 hours |
| @dr_zhumanova/1381 · this entry31 Jul 2026, 05:28 UTC | @drugaya_ginekologiya/11243 Aug 2026, 12:00 UTC | 1.00 | 3 days |
| @dr_zhumanova/1382 · this entry1 Aug 2026, 09:18 UTC | @drugaya_ginekologiya/11254 Aug 2026, 04:36 UTC | 1.00 | 3 days |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @drugaya_ginekologiya | 12 (8/8 hand-verifiable sample passed) | 1.00 | 2 days | this entry (11–1) |
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 1 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 17 comparable posts for this entry, running 17 July 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Across the whole group of 2, the earliest publisher we hold is @drugaya_ginekologiya. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, last confirmed 7 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Aug 2026, 00:12 | 12,291 | +2 |
| 11 Aug 2026, 02:05 | 12,289 | -4 |
| 10 Aug 2026, 04:10 | 12,293 | +7 |
| 9 Aug 2026, 04:11 | 12,286 | -5 |
| 8 Aug 2026, 01:13 | 12,291 | +6 |
| 7 Aug 2026, 10:15 | 12,285 | no change |
| 7 Aug 2026, 10:04 | 12,285 | first reading |
22 posts held, back to 17 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 15 pagesof Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 12 August 2026 |
|---|---|
| Posts held | 22 (17 July 2026 – 12 August 2026) |
| Views total | 51,635 |
| Reactions total | 789 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 12:32 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.
Lifetime counters from Telegram’s own channel header, read 12 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Measured directly from 16 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.
789 reactions across 22 posts, in 7 distinct kinds. The most used accounts for 59.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 468 | 59.3% | |
| 👍 | 256 | 32.4% | |
| 🔥 | 26 | 3.30% | |
| 🤯 | 15 | 1.90% | |
| 😁 | 14 | 1.77% | |
| 👌 | 6 | 0.76% | |
| 💯 | 4 | 0.507% |
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 22 of the 22 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 789reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 22 most recent posts we hold, published 17 July 2026 to 12 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.
Как не выбросить деньги на бесполезные анализы? Одни из самых частых и дорогих исследований, которые женщины сдают просто "на всякий случай", на самом деле могут быть бесполезны, если не знать простых правил. В этом видео я рассказываю, почему стоит отнестись с осторожностью к комплексам "женское здоровье" и как не выбросить деньги на ветер. Посмотрите, возможно, это сэкономит вам не только бюджет, но и время 🩺 💬 …
❤16👍6
Молочница возвращается: расскажу настоящую причину. Многие женщины сталкиваются с этой проблемой снова и снова. Кажется, что она уходит, но проходит время и возвращается. Причину часто ищут в иммунитете, стрессе или даже партнёре. Но на самом деле корень проблемы может быть куда проще и конкретнее. В видео я объясняю, почему молочница не уходит раз и навсегда и что мешает избавиться от неё окончательно 🩺 Посмотр…
👍17❤12👌1
Запах — это нормально? Да, но не любой У каждой женщины есть свой запах, и в этом нет ничего странного. Природа так устроила. Но есть важный нюанс: запах должен быть едва уловимым, а не резким. Когда он меняется это уже повод обратить внимание. И часто женщины недооценивают этот симптом, хотя для врача он может быть одним из ключевых. О том, как распознать тревожные сигналы и почему не стоит игнорировать изменения,…
❤22👍10
Внешняя красота начинается изнутри. Почему изменения во внешности, самочувствии, весе, состоянии кожи и качестве жизни женщины не всегда можно решить только косметологией или только гинекологией? ✅ 25 августа с 18:00 до 21:00 приглашаем Вас на круглый стол: «Внешняя красота как результат внутреннего здоровья. Откровенный разговор гинеколога с эндокринологом» Это будет не просто лекция, а живой разговор двух специа…
❤21👍8
Сон, который не восстанавливает: почему это происходит и что с этим делать? Нарушение сна — одна из самых частых жалоб, которую я слышу от женщин, особенно в возрасте 40+. Кто‑то долго не может уснуть, кто‑то просыпается в 4 утра и не смыкает глаз, а чей‑то сон становится поверхностным и утром нет чувства отдыха. Часто мы связываем это с гормонами и отчасти это так. Но причина почти всегда глубже. О том, почему та…
👍23❤13
☀ Наконец-то несколько дней без звонков, операционных и графиков. ❤ Отдыхаю, перезагружаюсь, набираюсь сил. Обещаю: скоро вернусь с новыми идеями и энергией ☀ Спасибо, что вы со мной даже в такие моменты ❤️ P.S. Отпуск, но я на связи и все Ваши вопросы и комментарии не останутся не отвеченными 😉
❤159👍57🔥26👌4
Если у вас был зуд, есть большая вероятность, что вы делали это неправильно Зуд — одна из самых частых и неприятных женских жалоб. И первое, что мы делаем, пытаемся решить проблему самостоятельно. Чаще всего наугад. И очень часто в итоге получаем не избавление от симптомов, а хроническую проблему, которая возвращается снова и снова. О том, почему привычный подход не работает и как не превратить зуд в бесконечную и…
❤24👍3
Почему с возрастом появляется «спасательный круг» у женщин и можно ли с ним что-то сделать? Знакомая ситуация: цифры на весах не меняются, а тело словно перестраивается само по себе. И вы начинаете искать причину в еде, нагрузках, гормонах… Но часто это комплексный процесс, который не сводится к одному фактору. Как адаптировать привычки, чтобы чувствовать себя лучше и почему 40+ это не приговор, а новый этап, рас…
👍33❤13
Выделения — это норма. Но не все знают, когда они становятся поводом насторожиться У каждой женщины они есть. И это абсолютно естественно. Но иногда организм подаёт сигналы, которые нельзя пропускать. Как понять, что всё в порядке, а когда пора обратиться к врачу — рассказываю в этом видео 🩺 Посмотрите, чтобы не гадать и знать, на что обращать внимание. 💬 А вы знали, какие выделения считаются нормой, а какие — не…
❤16
«Менструальный цикл и гормоны женщины нужно чувствовать» 🔼 Фраза, которую я услышала от своей мамы, она акушер - гинеколог. И с годами я всё чаще понимаю: это не просто красивые слова. В этом видео я говорю про фразу, которую не люблю, но сама иногда произношу) ⏩ Гормональный сбой. Почему это не диагноз и что скрывается за этим скрывается, рассказываю в видео. Посмотрите, чтобы перестать гадать и начать понимать …
❤30👍10
Posted without readable text
❤3
💎На канале новое видео💎 Женщины описывают выделения очень по-разному: белые, жёлтые, творожистые, пенистые, «грязные», с запахом или без. Но что из этого действительно говорит о заболевании, а что может быть вариантом нормы? 🤍 В этом видео я наглядно показываю разные виды выделений и объясняю, какие из них могут появляться в разные фазы цикла, а какие встречаются при молочнице, бактериальном вагинозе, воспалительны…
❤11👍2
Showing the 12 most recent of 22 posts we hold for @dr_zhumanova. 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.
Citation-graph rank — 339,814 of 1,151,006entries 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.
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.
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 12 August 2026 — this entry's latest reading, not the date you are reading this.
“Dr. Екатерина Жуманова” (@dr_zhumanova), 12,291 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/dr_zhumanova.
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.