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 53% 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 41 days, net +736. 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 9,353–10,704 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
18 Sept 2026, 02:58
10,245
-303
16 Sept 2026, 00:00
10,548
+322
14 Sept 2026, 09:16
10,226
-187
12 Sept 2026, 14:59
10,413
-14
10 Sept 2026, 16:18
10,427
-90
7 Sept 2026, 16:36
10,517
+265
4 Sept 2026, 15:41
10,252
-6
2 Sept 2026, 23:36
10,258
-12
2 Sept 2026, 00:55
10,270
-8
1 Sept 2026, 02:34
10,278
+468
29 Aug 2026, 04:02
9,810
+217
26 Aug 2026, 07:25
9,593
-29
23 Aug 2026, 02:05
9,622
-161
19 Aug 2026, 19:57
9,783
-145
16 Aug 2026, 17:44
9,928
+345
13 Aug 2026, 12:45
9,583
-266
10 Aug 2026, 23:02
9,849
-31
8 Aug 2026, 03:58
9,880
+371
7 Aug 2026, 16:15
9,509
no change
7 Aug 2026, 16:05
9,509
first reading
Engagement
9 posts held, back to 21 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 35 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
0.761%
avg views ÷ 10,245 subscribers
Avg views / post
78.0
1 post measured
Reaction rate
74.4%
reactions ÷ views · ER floor
Posts in window
1
of 9 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 28 August 2026
Posts held
9 (21 July 2026 – 28 August 2026)
Views total
78
Reactions total
58
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
29 Aug 2026, 05:02 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
Video runtime
1m 28s
Average length
15s
Measured directly from 6 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
1,370 reactions across 9 posts, in 17 distinct kinds. The most used accounts for 32.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
440
32.1%
🔥
373
27.2%
🎉
279
20.4%
🥰
64
4.67%
🤗
48
3.50%
👏
41
2.99%
🙏
23
1.68%
🏆
20
1.46%
⚡
18
1.31%
😱
18
1.31%
🍓
9
0.657%
😍
9
0.657%
🤩
8
0.584%
🍾
6
0.438%
😢
6
0.438%
💯
4
0.292%
😇
4
0.292%
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 9 of the 9 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 1,370 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 9 most recent posts we hold, published 21 July 2026 to 28 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.
Мои покупки в тайской сефоре🥰
Любимые бренды, которыми я пользуюсь всю жизнь.
Особенно Sol de Janeiro - единственный крем для тела, который покупала не раз🤎(не считая баттеры the body shop, которые в школе скупала тоннами). Просто обожаю 🤩
Скульптор Makeup by Mario просто обалденный 🥰 это я как обычно докопалась до консультанта, чтобы мне нашли самый лучший
Единственное, впервые познакомилась с корейским Then I M…
Всю рабочую неделю ждали субботы, чтобы поехать в океанариум Aquaria Phuket 🐬 Показать Роме рыбок и сделать красивые фото.
Только собиралась снять, как Рома уснул на руках в такси (уникальный случай) и что у тайцев вообще нет понятия “автокресло”. Как вдруг Рому резко стало рвать, как обычно катастрофически много, едва успели подставить рюкзак. Мы с Ромой испачкались с ног до головы, испачкали сиденье.
Водитель сра…
Вынуждена признать, что я в клубе «после года сложнее» 🌟
Рома был подарочным малышом - никогда не плакал подолгу, много спал, хорошо ел, играл в манеже часами.
До года 😈
Потом он пошел и началась жесть - сепарационный кризис, цепляется за ноги, нон-стоп просит внимания, плачет просто со всего. В коляске сидеть не хочет. Поехать куда-то тяжело. Везде истерики - в кафе, в тц, в машине. От еды стал отказываться и рас…
Наши выходные начались с химчистки 😀
Рома стащил мой перманентный маркер, а дальше все как в тумане.
Пострадали диван, плед, деревянно-стеклянный стол и как назло «та самая футболка на выход» 🥲
🟤Как справилась? Ведь период фломастеров не за горами, вдруг попадутся спиртовые
Главное правило - не тереть пятно, оно сразу расходится по всей ткани. Просто промокаем, выжимаем дурацкое пятно.
Универсальные средства, ко…
9-часовой перелет с малышом 🤩
Летели с Аэрофлот, сам полет 💯 - вовремя, плавный взлет, мягкая посадка, минимальная турбулентность над водой, большая медиа-библиотека, часто кормят, наливают вино, дают тапочки, беруши и маску.
У меня нет аэрофобии, я просто обожаю летать, но такие идеальные полеты все равно всегда отмечаю ✈️
❤️ Как сидеть?
Для малыша мы предварительно выкупили отдельное место, сделать это можно то…
Это были очень сложные несколько недель. Утомительные сборы, бюрократия, решение всех медицинских и юридических вопросов, вечный мониторинг радаров, прорезывание моляров у Ромы, от которых он до сих пор кричит ночами по несколько часов, и как назло прибавилось столько работы, что приходилось аж на несколько часов уходить из дома 🍃 (я с первого дня работала «несколько договоров в день», а с 6 мес это стала полноценная…
Мои призы в Игре по подготовке к родам от Школы материнства 🤎
Я в этой лодке уже давно 🛌
с большим удовольствием играла и ждала розыгрышей
Вот, что я выиграла:
🟤матрасик-гнездышко
🟤конверсы
🟤антибактериальная соска
🟤уходовый набор belly mom
🟤пазл-тач от bert toys
🟤набор одежды для новорожденного
🟤сет пробиотиков Lactoflorene
🟤комфортер Мякиши
🟤конверт с подушкой для новорожденного х2
🟤топ для кормящих от Kapusta fa…
🔥67❤63🎉43🏆14🍓8⚡5🥰5
Showing the 9 most recent of 9 posts we hold for @ch_nebesnaya. 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
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 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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“𝙽𝙴𝙱𝙴𝚂𝙽𝙰𝚈𝙰” (@ch_nebesnaya), 10,245 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/ch_nebesnaya.
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.