可爱的言欣宝贝炸号了,这是她的新号; @yanxinbaobao 期待和她的下一次见面……
❤4👍1🔥1

Channel
@Doctor9527CJRebirth
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Posts edited after publishing · Posts recorded as deleted · Polls · Citations · Handles named that no longer answer · Cite this entry
29,987subscribers
+6,049 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1002108043838 |
|---|---|
| Type | Channel |
| Username | @Doctor9527CJRebirth |
| Description | Doctor的出击回忆录 老师形态各异,灵魂异常有趣 |
| Created | Between 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 12 November 2026 |
| Measurements held | 63 |
| Confirmed unchanged | 1 time, most recently 12 November 2026 |
| On Telegram | t.me/Doctor9527CJRebirth |
Adult — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 80% 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 |
|---|---|---|
| 12 Nov 2026, 18:09 | 29,987 | +89 |
| 10 Nov 2026, 12:10 | 29,898 | +23 |
| 8 Nov 2026, 20:46 | 29,875 | +50 |
| 7 Nov 2026, 09:49 | 29,825 | +80 |
| 6 Nov 2026, 06:31 | 29,745 | +71 |
| 5 Nov 2026, 03:19 | 29,674 | +145 |
| 4 Nov 2026, 03:17 | 29,529 | +88 |
| 2 Nov 2026, 23:36 | 29,441 | +69 |
| 1 Nov 2026, 23:34 | 29,372 | +159 |
| 1 Nov 2026, 00:17 | 29,213 | +3 |
| 31 Oct 2026, 03:11 | 29,210 | +66 |
| 30 Oct 2026, 04:49 | 29,144 | -10 |
| 29 Oct 2026, 04:18 | 29,154 | +88 |
| 28 Oct 2026, 01:38 | 29,066 | +91 |
| 26 Oct 2026, 22:09 | 28,975 | +46 |
| 25 Oct 2026, 23:19 | 28,929 | +45 |
| 25 Oct 2026, 00:38 | 28,884 | -1 |
| 24 Oct 2026, 02:17 | 28,885 | +119 |
| 23 Oct 2026, 00:26 | 28,766 | +58 |
| 21 Oct 2026, 22:31 | 28,708 | first reading |
63 posts held, back to 2 August 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 180 pages 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 14 November 2026 |
|---|---|
| Posts held | 63 (2 August 2026 – 14 November 2026) |
| Views total | 171,020 |
| Reactions total | 1,676 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 14 Nov 2026, 20:09 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 14 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Measured directly from 38 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.
5,725 reactions across 63 posts, in 11 distinct kinds. The most used accounts for 57.2% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 3,277 | 57.2% | |
| 👍 | 2,284 | 39.9% | |
| 🔥 | 129 | 2.25% | |
| 🤡 | 15 | 0.262% | |
| 🎉 | 9 | 0.157% | |
| 🤨 | 3 | 0.052% | |
| 🖕 | 2 | 0.035% | |
| 😁 | 2 | 0.035% | |
| 😱 | 2 | 0.035% | |
| 👏 | 1 | 0.017% | |
| 🤩 | 1 | 0.017% |
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 63 of the 63 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 5,725 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 63 most recent posts we hold, published 2 August 2026 to 14 November 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.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @Doctor9527CJRebirth. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 63 most recent posts we hold for this entry, published 2 August 2026 to 14 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Telegram’s own ‘edited’ marker: 1 of 19 posts held from the last 30 days (5.26%) 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).
可爱的言欣宝贝炸号了,这是她的新号; @yanxinbaobao 期待和她的下一次见面……
❤4👍1🔥1
【Doctor的奇幻之旅之MMK】 【车牌】#MMK @chrischan199 【价格】599-50 报成都学院或者医生锅锅直接减50 【体验】我与小祁,也是历经波折,终于还是见面,内心OS:其实我还是想狠狠ntr星星哥,毕竟他是我的亲朋挚爱,手足兄弟,爱他,那就必须把爱他的所有,当然也包括她爱的人,毕竟我是一个深情的人,属实是爱屋及乌; 距离上一次MMK,已经过去一年多的时间,过去的这一年,我业已忘却怎样和MMK妹妹相处,显得无比稚嫩; 深秋的成都,已经带上些许的凉意,绿灰色假发,美丽的妆容,黑色漏胸针织衫,黑色短裤,过膝黑丝,黑色高跟小皮鞋,一眼我就看到她,她也一眼看到我,漂亮的她搭配着漂亮的衣服,显得她,愈发漂亮; “小祁,我不知道MMK是个啥流程,你要引导我哦” “医生哥哥,我知道就行”,她这样回我; 我们终于见面,见着她,我就知道,找她简直太对了,星星哥严选,我爱星星哥; 我们一起坐到沙发上,她摸着…
❤104👍70🔥2
#啾啾 @jiu520jiu99 这是我和她的第三次见面; “宝宝,我来找你了哦”,她老早就给我发了信息; 提前一天就约好了1点见面,可惜因为事情耽误了四十多分钟,她等了我快一个小时; 我紧赶慢赶,她还是在我们约定的地方等着我,带着一顶奶白色的毛茸茸猫猫帽子和一双猫猫手套,白色针织外套,浅咖色波波裙子,穿着光腿神器的大腿下面是一双小白鞋,她就这样俏生生的站在那等着我; 我走到她的面前,我看着她,她看着我,彼此相望; “私密马赛,红果泥私密马赛”,边对着她说着,边帮她拿手机,和零食(给我买的蛋挞和面包),腾出她的手,我与她,终于可以牵在一起; “刚刚两个人找我加微信,天呐,我好尴尬呀”,她说的我又是一顿愧疚,害她等我那么久; “那证明你魅力太大,自然就吸引了人”。 一路上她都在跟我腻歪,问我为啥微信不回,问我有没有想她,问我有没有变得更漂亮; 她,变得更加甜美,愈发粘人,也更像女朋友; 进了酒店,她就抱住了…
❤54👍37🤡2🔥1
生活中我们多一点相互关爱,少一点戾气,遇见好老师就多去; 最重要的是,多说:红果泥私密马赛……
❤30👍7🔥2
【花名】#黎吧啦 【车牌】@libalabao 【价格】10P/16PP #报成都学院写报告减1 【验证】 Doctor 【评分】Doctor ’s体验分析报告→黎吧啦:8.43 【硬件】在深圳长大的武汉妹妹,22岁左右,自述大四未毕业,视频本人,人照8分,本人和照片打扮一样,大黑框眼睛,棒球帽,本人没有视频甜美,本人摘下眼镜之后更加御姐一点,身高170,体重100,胸C,挺拔无科技,豆豆小,乳晕较大,全身无赘肉,但也不是排骨精,全身无纹身,皮肤光滑细嫩,肤质很好,皮肤偏白,乳晕都豆豆颜色都是粉色,下面工人白虎,颜色浅褐色,可以归于粉色,G点凸出很高,馒头逼,下面有蝴蝶,进入之后,褶皱感和包裹感很明显,会夹; 【软件】大蟒蛇、三件套、69、制服等课表内容,口技加分 【体验】今天依旧是深秋成都难得的充满阳光的好天气; 见到她的时候,她已经在路边等我,和照片一样的大黑框眼睛,棒球帽,虽然没有照片甜妹,但也充满青春女大…
👍165❤135🎉2🔥2
📍成都会所半套全套海选 📢成都会所 半套 全套 海选 📢不办卡不充值没有隐形消费 成都100家门店 📍提供位置就近安排 全城预约安排 联系老表预约 @chengdu299BOT 半套均价500~700明码标价具体咨询客服 全套均价1000~1500明码标价具体咨询客服 #成都半套 #成都全套 #成都莞式服务 #成都口爆 #成都95 #成都98 #成都一条龙 #成都海选 🈺业时间:中午2:00-凌晨4:00 情人式服务: 裸吹/共浴/丝袜/按摩 口·真颜值/直度配合 丝袜 制服 鸳鸯戏水 配合度拉满 微信: chengdu050 QQ: 1093656650 预约客服 @chengdu299 会所频道 @zhuhai7188 成都会所—修车觅蚌交流群 https://t.me/CHDKTV
❤32👍24🔥2
【花名】#白芷 【车牌】@xhl19123 【价格】6P/10PP 【验证】 Doctor 【评分】Doctor ’s体验分析报告→白芷:8.46 【硬件】08年的重庆妹儿,第一个白t黑色针织外套视频,人照8.3,本人是可爱的甜妹类型,身高165左右,体重98左右,胸C,很挺,无下垂,竹笋状,乳晕和奶头中等偏小,全身无赘肉,脸蛋光洁无痘痘,全是无纹身,后背应该是那种油痘体质,乳晕和豆豆都是很浅的褐色,下面毛量中等偏少,浅褐色,小蝴蝶,进入后褶皱感和包裹感比较强烈,水也属于越夺越夺,会自然呻吟和咬舌头,脖子和胸很敏感,各种姿势都很配合,整体doi的感觉不错; 【软件】大蟒蛇、三件套、69、制服、舔胸等课表内容,但是不熟悉 【体验】其实今天是双飞,可惜,只夺了白芷,她的姐妹洗完澡,吃了嘴子,结果红了,简直达咩; 那就专心致力于白芷,教她怎么亲吻,教她怎么舔胸,教她怎么挑逗两人的情绪,她也在努力的学习; 洗完澡之后三…
❤126👍64🔥3
【花名】#小野 【车牌】@Xiaoye52010 【价格】7P/12PP 【验证】Mystery 【评分】Mystery’s体验分析报告→8.37 【硬件】河南妹妹,人照8.5,年龄22,冷白皮,身高160左右,体重95,胸B,身材较为匀称,大腿还是有点肉,全身无纹身,乳晕和豆豆正常大小、正常褐色,逼型为蝴蝶,毛量较多,外侧正常褐色,内侧粉嫩。 【软件】舌吻+三件套,大蟒蛇,能一直蛇,蛇蛇精有福了,口的力度感觉较为轻微,但时间长,看个人喜不喜欢这种口的方式,服务态度好,无机车行为,帮擦水分等细节做得也很到位,会聊天,会照顾你的心情,情绪价值很高,即使是i人也能有很不错的体验,不抽烟。 【体验】来了,出发之前医生锅锅就给我说小野是老牌老师了,我就知道这一把应该问题不大,怀着期待的心情来到南站这边只来过一次的酒店,这个酒店环境也还可以,比高升桥好。 进门看着小野人照差别不大,大眼睛,给人一种可爱的感觉,就是最近她脸上…
❤96👍64🔥12🎉1
【花名】#悠悠 【车牌】@uouu688 【价格】8P/14PP #报成都学院写报告减1 【验证】 Doctor 【评分】Doctor ’s体验分析报告→悠悠:8.43 【硬件】四川妹妹,人照8.5分,22岁,照片甜妹,本人御姐,见我的时候,黑色西装,牛仔裤,很御,也很欲,身高165,体重98,胸B,乳晕和豆豆中等大小,大屁股,不是我喜欢的排骨精,但是应该是本群绝大多数人喜欢的那种身材,除了胸,该有肉的地方全有肉,但是又一点也不胖,全身皮肤中等颜色,大腿有个纹身,不算大,乳晕和豆豆颜色中等褐色,下面毛量很多,很旺盛,外褐内粉,下面松紧度中等,有包裹感和褶皱感,但是很浅,女上的时候,一直能顶到她的里面,感觉她的里面在不停的呼吸,做爱反馈很好,今天完完整整桩了30分钟,中间我都喊停了说不做了,反正就是不行,必须要做; 【软件】大蟒蛇、三件套、69、制服等课表内容 【体验】小青的闺蜜,悠悠,都是商K出生的妹妹,情绪价值这…
❤82👍49🔥5😁1
#言 @yh188288 这不知道是第几次和她见面了,每次和她见面,激烈过后都是平静的湖面,她,总能抚平我心中的那些波澜,也许这就是我愿意和她呆在一起的原因; 我也觉得很奇怪,为什么能约她这么多次,我与她可能不只是生理上的喜爱,可能就是单纯的喜欢和她呆在一起,轻松,抛却烦恼,没有忧虑; 是欢愉之后,她躺在我的怀里,诉说着最近彼此的生活和对生活的感悟; 是吃饭之时,我与她相向而坐,讨论这桌上的菜肴怎样的美味和健康; 是用餐之后,牵手走在人行道,讲述着对人生的规划和对婚姻的期待与恐惧; 也许,这就是与她在一起的点点滴滴,有生理上的喜欢,更多的可能是喜欢和她在一起时能在这个充满压力的生活中,稍微的给自己一口能够喘息的契机; 她,很难得,也许我们还会见很多次,但肯定不会像万物见一百多次,毕竟我是博爱的,就酱; 以上,共勉~~~~~~ 👉【成都学院】👈,车库老师八折报销
❤13👍7🔥1
绝色 (兼职)专线 (宁缺毋滥) 首次学习做号 大家共同见证成长 本号只做高质量 把个体通过筛选留下,只为给大家提供更多的方便,更精确到质量 颜值和身材只是最基本的门栏,长期的口碑 良好的风评才是我们所追求的浪漫 你看的不是菜单,是独属于你一人的片刻柔情 联系 @kuaidi00001 车库 @jusecheku01 双向 @xiaoxiao4628bot
❤37👍31🔥1
鉴于很多同学看了我包养的两个妹妹之后,对于包养有很多疑问,因此我单独做一期包养攻略; 1、介绍费如何支付? 回复:包养介绍费是确定好要见的包养妹妹之后,平台收取介绍费,然后安排和看上的妹妹见面,见面不满意,不要加联系方式,直接反馈给平台,平台安排下一个妹妹,千万不要来都来了感觉差不多就定,多看几个,找到自己最喜欢的那个。如果确定好是看上的妹妹,那就可以加上联系方式,本次包养平台介绍也就结束了,如果下次还想换其他妹妹,那就重复以上流程。 2、见妹妹有哪些流程? 回复:其实就和约炮差不多,只是比约炮更加直白,妹纸也清楚知道她要啥,你也清楚妹纸想要啥,第一次见面可以在商场、咖啡店、奶茶店等公众场合,不要第一次就见面吃饭这样的,是能尽快抽身的场合,毕竟万一看不上妹纸也好体面的离开;见面之后,如果看不上妹妹,那就给她来回车费,让她走;如果看得上,就可以和她聊具体陪伴时间,地点,了解需求,比如要她准备学信网资料,体检资料等,了解完这…
❤34👍11🔥1
Showing the 12 most recent of 63 posts we hold for @Doctor9527CJRebirth. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
@Doctor9527CJRebirth edited 4 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
We recorded 22 posts on @Doctor9527CJRebirth as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
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The shares total 102%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 63 most recent posts we hold, published 2 August 2026 to 14 November 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
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.
Named by 20 registered channels — 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.
@Doctor9527CJRebirth 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.
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
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 November 2026 — this entry's latest reading, not the date you are reading this.
“Doctor的诊断记录” (@Doctor9527CJRebirth), 29,987 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/Doctor9527CJRebirth.
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.