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Channel

成都医科大学上牌车库

@shangpailaoshi

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Posts recorded as deleted · Citations · Cite this entry

43,948subscribers

+19,522 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1002860580449
TypeChannel
Username@shangpailaoshi
Description成都医科大学修车群: https://t.me/chengdu338 验证老师不等于百分百真人,若发现货不对板务必转身并联系管理 上牌:商务合作或提交报告联系 : @lyihstzw 双向机器人 @Yike55688_bot
CreatedBetween 1 June 2025 and 30 September 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live7 November 2026
Measurements held61
Confirmed unchanged1 time, most recently 7 November 2026
On Telegramt.me/shangpailaoshi

Topic

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 10 September 2026 and assigned it the closest of 31 fixed categories, at 69% 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.

Growth

24,42643,94834,1876 August 20267 November 2026
61 measurements spanning 93 days, net +19,522. 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 21,498–46,876 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 61
Measured (UTC)SubscribersChange
7 Nov 2026, 09:4843,948+191
6 Nov 2026, 09:3843,757+392
5 Nov 2026, 07:1143,365+438
4 Nov 2026, 09:4042,927+435
3 Nov 2026, 09:0942,492+319
2 Nov 2026, 10:0642,173+490
1 Nov 2026, 06:3641,683+288
31 Oct 2026, 09:2841,395+438
30 Oct 2026, 06:5740,957+411
29 Oct 2026, 06:4640,546+612
28 Oct 2026, 02:3839,934+371
27 Oct 2026, 00:4639,563+381
25 Oct 2026, 22:5539,182+385
25 Oct 2026, 01:4538,797+370
24 Oct 2026, 02:5038,427+304
23 Oct 2026, 02:4038,123+345
22 Oct 2026, 01:5037,778+187
20 Oct 2026, 23:5937,591+337
20 Oct 2026, 01:4737,254+349
19 Oct 2026, 03:1536,905first reading

Engagement

207 posts held, back to 4 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 155 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
1.63%
avg views ÷ 43,948 subscribers
Avg views / post
716
78 posts measured
Reaction rate
0.158%
reactions ÷ views · ER floor
Posts in window
78
of 207 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. It is computed over the 40 of 78 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 8 November 2026
Posts held207 (4 August 2026 – 8 November 2026)
Views total55,838
Reactions total50
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Nov 2026, 05:33 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

Photos
≈3,890
Videos
≈220
Links
≈745

Lifetime counters from Telegram’s own channel header, read 8 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.

Video runtime
5m 14s
Average length
10s

Measured directly from 31 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

169 reactions across 100 posts, in 6 distinct kinds. The most used accounts for 91.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤15491.1%
👍84.73%
👎42.37%
👏10.592%
🔥10.592%
😁10.592%

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 117 of the 207 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 169 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 207 most recent posts we hold, published 4 August 2026 to 8 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.

Recent posts

Telegram’s own ‘edited’ marker: 15 of 78 posts held from the last 30 days (19.2%) 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).

8 Nov 2026, 04:57 UTC98 viewsread 8 November 2026
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【成都医科大学认证车库】 花名: #甜宝 车牌: @CDTB1023 车费: #6/9 位置: #交子大道 标签: #武侯区 #御姐 #自聊 #态度车 #服务车 #身材车 注:老师25岁 ,身高165,体重55kg,身材好,身上有训练痕迹,隐隐约约看得到腹肌,服务有背面过水,按摩,正面舔胸,口,舔蛋,倒立口交,有小玩具可以体验,并且可以抠逼。爱爱反馈真实,下面很紧,会夹,女上功夫了得,射了都在继续夹。态度好有情绪价值,总体吃身材和服务的狼友推荐 体验报告汇总 :@chengduainila 上牌或提交报告联系 : @lyihstzw 双向机器人: @Yike55688_bot 注:好评报告五篇上已验红牌榜差评过多下榜反馈请直接联系管理员 @Yike55688_bot 成都医科大学聊天群:@chengdu338 #成都电报 #成都楼凤 #成都修车

8 Nov 2026, 03:17 UTC172 views1 reactionsread 8 November 2026
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【成都医科大学认证车库】 花名: #徐冬冬 车牌: @yezi030305 车费: #6/10 位置: #衣冠庙 标签: #武侯区 #少妇 #自聊 #服务 #态度车 #身材车 注: 老师162 50kg 人照8.5分 梨形身材微胖 有点小肚子 38D巨乳 乳晕大 蝴蝶逼 水多 比较紧 夹腿后无敌紧 无异味 老师服务非常到位,熊莎,乳交,口活,海底捞月,毒🐉都是一绝,差点被口出来。 态度非常好,服务做得很久,一点也不催,做爱还会撒娇,情绪价值给到位了 体验报告汇总 :@chengduainila 上牌或提交报告联系 : @lyihstzw 双向机器人: @Yike55688_bot 注:好评报告五篇上已验红牌榜差评过多下榜反馈请直接联系管理员 @Yike55688_bot 成都医科大学聊天群:@chengdu338 #成都电报 #成都楼凤 #成都修车

👍1

7 Nov 2026, 08:43 UTC522 viewsread 8 November 2026
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📊 0条车评 写报告 好评 0% | 人照 | 服务 中评 0% | 颜值 | 态度 差评 0% | 身材 | 环境 【成都医科大学认证车库】 花名: #宝儿 车牌: @cd02888 车费: #4/7 位置: #建设路 标签: #武侯区 #成华区 #天府二街 #工作室 #嫩妹 #御姐 #代聊 #双流 注:东门建设路 / 南门天府二街 / 北门昭觉寺 备注:公寓式酒店,私密性高,无定金,无套路 满意在付💰,不办卡,不充值。 预约联系: @cd02888 双向机器人 : @CDbaoer028bot 与你随时在线:cd095098 两分钟没回致电:18144340869 频道 https://t.me/chengdubantao398 体验报告汇总 :@chengduainila 上牌或提交报告联系 : @…

6 Nov 2026, 11:55 UTC806 viewsread 8 November 2026
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📊 1条车评,综合分 8.8 好评 100% | 人照 8.5 | 服务 9.0 中评 0% | 颜值 8.5 | 态度 9.0 差评 0% | 身材 9.0 | 环境 9.0 👆 【点击查看评价】 【成都医科大学认证车库】 花名: #木子 车牌: @muzimm1 车费: #8/13 位置: #索尔龙舟 标签: #锦江区 #御姐 #自聊 #态度车 #身材车 #大蟒蛇 #上门 注: 注明老师身高165左右,年龄二十七八,体重90多斤,身材匀称,人照8.5分,身材比例很好,大长腿、胸C,天然胸,手感好,皮肤光滑细腻,肤色很白、屁股大有肉,后入很爽,无赘肉,咪咪浅褐色,下面蝴蝶穴。外褐内粉,湿度很湿,紧度比较紧,,毛量不多,服务挺多的,态度也非常好,会帮你按摩,全身漫游,亲安逸,口,亲咪咪,舔蛋蛋,无异味。 体验报告汇总 :@chengduainila 上牌或提交报…

5 Nov 2026, 14:12 UTC977 viewsread 8 November 2026
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📊 1条车评,综合分 8.3 好评 100% | 人照 7.0 | 服务 9.0 中评 0% | 颜值 8.0 | 态度 9.0 差评 0% | 身材 8.5 | 环境 8.5 👆 【点击查看评价】 【成都医科大学认证车库】 花名: #白微微 车牌: @baiweiwe 车费: #5/8 位置: #玉林路 标签: #武侯区 #少妇 #自聊 #态度车 注: 老师26岁 身高160 体重90,胸B,毛多逼褐,人照7分像,颜值还行。进门老师还是很热情的,会聊天,帮洗澡,手法和口技不错,口的时间久,皮肤光滑。接受各种姿势暴力输出。缺点:不敢69,下面味道很重,像是用了某种洗液,手摸了下,味道一直散不去。总体来说,喜欢服务车态度车的老表可以冲 体验报告汇总 :@chengduainila 上牌或提交报告联系 : @lyihstzw 双向机器人: @Yike5568…

5 Nov 2026, 13:37 UTC757 viewsread 7 November 2026
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Telegram必备的搜索引擎,极搜JISOU帮你精准找到,想要的群组、频道、视频、音乐 👉 t.me/jisou2?start=a_7593294667

5 Nov 2026, 13:37 UTC766 views1 reactionsread 7 November 2026
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【成都医科大学认证车库】 花名: #舒月 车牌: @shuyue09 车费: #5/8 位置: #红牌楼 标签: #武侯区 #自聊 #御姐车 #颜值车 #服务车 #5p 注:该老师年龄23,皮肤白手感光滑,身材前凸后翘,摸起来手感很棒,下面正常,小穴蝴蝶B,水量偏多,有包裹感,胸的话天然是B+,坚挺摸着手感很棒,服务有陪洗,水中箫,口,大蟒🐍,舔mimi,69,爱爱等,床上很配合,会主动喊后入式,日感没的说,态度还好情绪价高,不催不油,pp更有性价比,综合体验值得推荐。 体验报告汇总 :@chengduainila 上牌或提交报告联系 : @lyihstzw 双向机器人: @Yike558_bot 注:好评报告五篇上已验红牌榜差评过多下榜反馈请直接联系 @Yike558_bot 成都医科大学聊天群: @chengdu338 #成都电报 #成都楼凤 #成都修车

❤1

4 Nov 2026, 15:34 UTC≈1,020 views2 reactionsread 7 November 2026
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📊 1条车评,综合分 6.7 好评 100% | 人照 9.0 | 服务 6.0 中评 0% | 颜值 6.0 | 态度 5.0 差评 0% | 身材 8.0 | 环境 6.0 👆 【点击查看评价】 【成都医科大学认证车库】 花名: #Miko 车牌: @cdMiko 车费: #5/9 位置: #东郊记忆 标签: #成华区 #少妇车 #代聊 #态度车 #洋马 注: 老师身高163,年龄24左右,体重90左右,人照8分,一眼认出菜单本人,菜单简单美白,真人泰国人,会简单中文,身材苗条,线条不错,后背满背纹身,胸B是假胸比较硬,奶头小三点颜色褐色,人工白虎,昆感一般,服务配合,卖力,爱笑,打了牙箍,态度好。陪洗细致认真,讲卫生。 体验报告汇总 :@chengduainila 上牌或提交报告联系 : @lyihstzw 双向机器人: @Yike55688_bot…

❤2

4 Nov 2026, 04:27 UTC937 viewsread 6 November 2026
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🎰 🔥🔥金惠抓龙筋联合医科大给兄弟们送福利啦 📮 参与条件: 🗺️ 区域限制:四川省 🎫 加入-成都抓龙筋金穗 🎫 加入-正宗泰式抓龙筋👍金穗 └💬 发言数大于 3 条 🎫 加入-成都医科大学上牌车库 🎫 加入-成都医科大学修车群 └💬 发言数大于 3 条 🎁 奖品内容: 💰️ 18口令红包 x 1 💰️ 399白嫖券 x 1 📆 定时开奖 北京时间:2026年11月09日 12时27分 👉 点击参与抽奖 🎁 点击查看更多抽奖

3 Nov 2026, 12:34 UTC957 views0 reactionsread 6 November 2026
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📊 0条车评 写报告 好评 0% | 人照 | 服务 中评 0% | 颜值 | 态度 差评 0% | 身材 | 环境 【成都医科大学认证车库】 花名: #Vera 车牌: @cdverababy 车费: #4/7 位置: #东郊记忆 标签: #成华区 #少妇 #代聊 #态度车 #身材车 #洋马 #按摩 注: 高挑服务型泰国少妇,人照8分像,年龄30左右,身高170,体重95斤左右,身材高挑匀称,精致短发,颜值中等,皮肤白皙光滑,天然b胸,乳头乳晕正常大小,颜色褐色,轻微小肚子,屁股有肉弹性好,人工白虎,包子批,颜色浅褐色,服务时间长力道足,主动泰式按摩,舔凶舔蛋,口活稍微狂野了一点,爱爱姿势配合度高,炮架子,叫声大销魂狂野,紧,水多,老师会一点点中文,交流无障碍,征服感满满。适合少妇控,服务控,腿控,皮肤控,紧控,感…

3 Nov 2026, 09:13 UTC808 views1 reactionsread 5 November 2026
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📊 1条车评,综合分 9.1 好评 100% | 人照 8.0 | 服务 10.0 中评 0% | 颜值 8.5 | 态度 10.0 差评 0% | 身材 8.0 | 环境 10.0 👆 【点击查看评价】 【成都医科大学认证车库】 花名: #菲莉娅 车牌: @fly3678 车费: #7/12 位置: #天府五街 标签: #双流区 #嫩妹 #代聊 #态度车 #舌吻 #深喉 #69 #敏感车 #骚话多 #夹子音 注: 老师身高165,体重49kg,人照不一致,真人是在校女大的一般颜值水平,今日妆浓腮红重,夹子音酥酥麻麻。皮肤正常黄皮,背部有痘痘,除手臂外比较光滑,仅肩部有小符文,手胸腿部有速胖/速瘦留下的生长纹。 b胸八字奶,非饱满类型,摸和吸着软和,腿部腹部正常无赘肉。下面毛量多,有阴唇漏出,浅逼较粉无异味,敏感水多不松,女上能流到蛋上那种,后入能把套子夹掉。 各项…

❤1

3 Nov 2026, 09:02 UTC740 views1 reactionsread 5 November 2026
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📊 1条车评,综合分 8.7 好评 100% | 人照 8.5 | 服务 9.0 中评 0% | 颜值 8.5 | 态度 8.0 差评 0% | 身材 9.0 | 环境 9.0 👆 【点击查看评价】 【成都医科大学认证车库】 花名: #小七 车牌: @xiaoqi200803 车费: #6/11 位置: #动物园 标签: #成华区 #嫩妹 #蟒蛇车 #女友感 #69 注: 172 19 100斤 人照8分身材不坦不苗条,身高真的高 奶子很大很粉,纹身有点多 手臂全是 屁股大,有点肉,下面粉嫩毛多水多紧,老师才来成都有点害羞,很听话可以对着镜子口,主要是嫩妹有毒龙 体验报告汇总 :@chengduainila 上牌或提交报告联系 : @lyihstzw 双向机器人: @Yike55688_bot 注:好评报告五篇上已验红牌榜差评过多下榜反馈请直接联系管…

❤1

Showing the 12 most recent of 207 posts we hold for @shangpailaoshi. 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.

Posts edited after publishing

@shangpailaoshi edited 7 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.

First edit seen
8 August 2026
Most recent edit
29 October 2026

Posts recorded as deleted after publishing

We recorded 2 posts on @shangpailaoshi 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.

First seen missing
10 October 2026
Most recent seen missing
28 October 2026
Median time before seen missing
35 hours
Seen missing in the last 30 days
2

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Republishes

Channels on the register whose posts this channel has forwarded.

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 7 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.

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 7 November 2026 — this entry's latest reading, not the date you are reading this.

“成都医科大学上牌车库” (@shangpailaoshi), 43,948 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/shangpailaoshi.

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.