❤️老师:016 🌃区域:汉口公寓 💸课费:550P 650PP 👙三维:身高158 体重90 胸b 💯标签:御姐 🎉特点:服务好人特别温柔,有耐心,回头率特别高,完全不烧心 📱客服: @hk95980 双向: @xt112bot 总群: http://t.me/whmtx520
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Channel
@wh95zx
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
1,008subscribers
+825 since we began measuring on 17 October 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1003968422849 |
|---|---|
| Type | Channel |
| Username | @wh95zx |
| Created | Between 1 April 2026 and 31 August 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 17 October 2026 |
| Last confirmed live | 7 November 2026 |
| Measurements held | 5 |
| Confirmed unchanged | 1 time, most recently 7 November 2026 |
| On Telegram | t.me/wh95zx |
Adult — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B, prompt version 1) read this channel’s own recent posts on 1 November 2026 and assigned it the closest of 31 fixed categories, at 52% 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 the other topics.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 7 Nov 2026, 09:24 | 1,008 | +112 |
| 1 Nov 2026, 01:27 | 896 | +229 |
| 25 Oct 2026, 20:35 | 667 | +484 |
| 17 Oct 2026, 22:21 | 183 | no change |
| 17 Oct 2026, 20:22 | 183 | first reading |
11 posts held, back to 28 September 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.
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 17 October 2026 |
|---|---|
| Posts held | 11 (28 September 2026 – 17 October 2026) |
| Views total | 381 |
| Reactions total | 23 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 17 Oct 2026, 20:22 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.
Measured directly from 3 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.
71 reactions across 10 posts, in 3 distinct kinds. The most used accounts for 64.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 46 | 64.8% | |
| 👍 | 17 | 23.9% | |
| 🔥 | 8 | 11.3% |
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 10 of the 11 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 71 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 11 most recent posts we hold, published 28 September 2026 to 17 October 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.
Telegram’s own ‘edited’ marker: 3 of 5 posts held from the last 30 days (60.0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
❤️老师:016 🌃区域:汉口公寓 💸课费:550P 650PP 👙三维:身高158 体重90 胸b 💯标签:御姐 🎉特点:服务好人特别温柔,有耐心,回头率特别高,完全不烧心 📱客服: @hk95980 双向: @xt112bot 总群: http://t.me/whmtx520
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Channel name was changed to «武汉小天甄选»
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🎀艺名:百灵 🌏城市:#武汉 🌃区域:汉阳区 💸课费:900P 1500PP 👙三维:02年 身高168 体重90 胸C 💯标签:御姐 🎉特点:扎着低马尾,几缕碎头发飘在额头。眼睛又大又水灵,脸上干干净净,嘴角浅浅带着笑,看着温柔大方。身上穿件卡其色外套,夜里路灯打在脸上,气质安静舒服,看着成熟稳重。 📱私聊:@bailing131421
❤7👍2
🎀艺名:小熊猫 🌏城市:#武汉 🌃区域:江岸区 💸课费:900P 1800PP 👙三维:03年 身高162 体重99 胸D+ 💯标签:御姐 大胸 🎉特点:乌黑顺滑的长直发,头上别了个带白点的粉色大蝴蝶结,花边是白色蕾丝。眼睛大大的,眼线细细拉长,脸蛋白白嫩嫩,唇色粉嫩。她对着镜头比 OK 手势,穿粉色蕾丝吊带,整个人甜得像小公主,又带点娇俏的小妩媚。 📱私聊:@xiaoxiongmao12323
❤7👍2
🎀艺名:小蜜 🌏城市:#武汉 🌃区域:洪山区 💸课费:600P 👙三维:08年 身高160 体重80 胸A+ 💯标签:嫩妹 甜妹 🎉特点: 棕调蓬松卷发,眼尾上扬,眼下一颗泪痣格外抓人。粉调腮红衬得眉眼浓烈,嘴角微松,带着漫不经心的媚,野性又亮眼。 📱私聊:@jvnjj08
❤4🔥4👍1
🎀艺名:小梦 🌏城市:#武汉 🌃区域:汉阳区 💸课费:900P 1500PP 👙三维:03年 身高165 体重100 胸C 💯标签:御姐 🎉特点:武汉小梦,23 岁,身高 165。留着乌黑顺滑的长直发,脸蛋小巧,眼型好看,清冷感十足 穿米黄色蕾丝抹胸 + 做旧牛仔短裤,腰很细,右臂有纹身。戴四叶草项链、细手链,拿印着爪印图案的手机对镜自拍,身材匀称,纯纯又带点小酷 📱私聊:@xiaomeng12111
❤7👍2🔥2
🎀艺名:奴娇 🌏城市:#武汉 🌃区域:汉阳区 💸课费:1200P 1600PP 👙三维:05年 身高172 体重102 胸B+ 💯标签:御姐 大长腿 🎉特点:武汉奴娇,05年,身高172,体重102,真胸大D蜜桃臀,身形高挑偏瘦。黑长直的长发,脸型精致,大眼睛,妆容柔和。手做了带豹纹装饰的长美甲,手上戴银戒指、串珠手串。气质又甜又冷,高挑骨架配上清秀长相,看着很亮眼。 📱私聊:@nujiao0
❤7👍3
🎀艺名:#热巴 💸课费:600P 1000PP 🌏城市:#武汉 🌃区域:江岸 💯标签: #御姐 📱私聊:@rebaba188 💕频道:https://t.me/renbaba698
❤6👍2
🎀艺名:#念念 💸课费:600P 1100PP 🌏城市:#武汉 🌃区域:洪山 💯标签: #嫩妹 📱私聊:@niannian0002 💕频道:https://t.me/niannian88856
❤4👍2
🎀艺名:#静香 💸课费:600P 1100PP 🌏城市:#武汉 🌃区域:洪山 💯标签: #嫩妹 📱私聊:@jingxiang2588 💕频道:https://t.me/jingxiang2668
❤2🔥2
Showing the 11 most recent of 11 posts we hold for @wh95zx. 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.
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.
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.
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 7 November 2026 — this entry's latest reading, not the date you are reading this.
“武汉小天甄选” (@wh95zx), 1,008 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/wh95zx.
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.