📊 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 原价出击请在群里输入提交报告,工兵请出击完请按【成都医科大学认证车库】 花名: #月月 车牌: @Yuey102 车费: #6/10 位置: #天府二街 标签: #武侯区 #少妇 #自聊 #感觉车 #身材车 #制服 注: 老师身高162,体重不到90,人照8分吧,去掉美颜就是本人。胸有C+,屁股没啥肉,整个细枝结硕果,腿长无赘肉。奶头粉色,下面浅褐色,馒头B,大阴唇巨小。水量旺盛,毛量正常。服务无敷衍,情绪价值。较高,女上永动机反馈明显。 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…

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 · Citations · Cite this entry
28,834subscribers
+4,408 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1002860580449 |
|---|---|
| Type | Channel |
| 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 |
| Created | Between 1 June 2025 and 30 September 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 17 September 2026 |
| Measurements held | 33 |
| Confirmed unchanged | 1 time, most recently 17 September 2026 |
| On Telegram | t.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 why it has no browse page of its own yet.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Sept 2026, 21:01 | 28,834 | +458 |
| 15 Sept 2026, 20:17 | 28,376 | +242 |
| 14 Sept 2026, 05:20 | 28,134 | +160 |
| 12 Sept 2026, 13:37 | 27,974 | +303 |
| 10 Sept 2026, 09:40 | 27,671 | +379 |
| 7 Sept 2026, 05:36 | 27,292 | +87 |
| 4 Sept 2026, 08:57 | 27,205 | +167 |
| 2 Sept 2026, 18:18 | 27,038 | +101 |
| 1 Sept 2026, 18:18 | 26,937 | +30 |
| 31 Aug 2026, 20:53 | 26,907 | +120 |
| 30 Aug 2026, 20:44 | 26,787 | +237 |
| 29 Aug 2026, 21:38 | 26,550 | +80 |
| 28 Aug 2026, 23:25 | 26,470 | +94 |
| 28 Aug 2026, 01:53 | 26,376 | +26 |
| 27 Aug 2026, 05:13 | 26,350 | +111 |
| 26 Aug 2026, 05:13 | 26,239 | +97 |
| 25 Aug 2026, 01:38 | 26,142 | +94 |
| 23 Aug 2026, 17:15 | 26,048 | +85 |
| 22 Aug 2026, 02:38 | 25,963 | +90 |
| 20 Aug 2026, 16:53 | 25,873 | first reading |
Engagement
93 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 64 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 2.66%
- avg views ÷ 28,834 subscribers
- Avg views / post
- 767
- 37 posts measured
- Reaction rate
- 0.173%
- reactions ÷ views · ER floor
- Posts in window
- 37
- of 93 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 23 of 37 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 23 September 2026 |
|---|---|
| Posts held | 93 (4 August 2026 – 23 September 2026) |
| Views total | 28,381 |
| Reactions total | 33 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 23 Sept 2026, 11:37 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
- ≈3,450
- Videos
- ≈199
- Links
- ≈656
Lifetime counters from Telegram’s own channel header, read 23 September 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
- 2m 00s
- Average length
- 11s
Measured directly from 11 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
66 reactions across 39 posts, in 3 distinct kinds. The most used accounts for 92.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 61 | 92.4% | |
| 👍 | 4 | 6.06% | |
| 😁 | 1 | 1.52% |
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 49 of the 93 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 66 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 93 most recent posts we hold, published 4 August 2026 to 23 September 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
📊 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: #欣欣 车牌: @xxin1520 车费: #6/10 位置: #天府二街 标签: #武侯区 #御姐 #自聊 #态度车 #身材车 注: 老师人照8.5分,身高165 体重100 、胸b身材很好无赘肉屁股小翘、毛量正常,嫩b很紧,水多,年龄29左右。老师服务认真专业,带点儿小高冷御姐感拉满。缺点是没有蛇和不能69挺可惜的,无任何机车行为 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管理员 @Yike558_bot…
📊 1条车评,综合分 8.7 好评 100% | 人照 8.0 | 服务 8.0 中评 0% | 颜值 9.0 | 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: #瑶瑶 车牌: @YaoYao123i 车费: #6/10 位置: #青龙广场 标签: #成华区 #嫩妹 #冷白皮 #大长腿 #三点粉 #良家感 #美胸 #代聊 注: 妹妹18岁,人照8.5,照片看着像御姐实际是嫩妹,冷白皮,胸特别白,菜单写b,感觉有c,颜值身材都不错,邻家小女孩初长成的样子,身高一米六左右乖乖脸,不是排骨精微微有肉感,但没有赘肉,态度很好,特别爱笑,各个姿势都配合但不是很会,服务比较少,但舌吻69都可以,主动提出来基本不会拒绝,之前爱爱经验应该不是很多 体验报告汇总 :@chengduainila 上牌或提交报告…
❤3
📊 1条车评,综合分 8.7 好评 100% | 人照 9.0 | 服务 8.0 中评 0% | 颜值 8.0 | 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: #小迪 车牌: @Tianoipo 车费: #6/10 位置: #青龙广场 标签: #成华区 #嫩妹车 #冷白皮 #大长腿 #三点粉 #良家感 #美胸 #刚下水 #紧 #水多 注: 小迪是邻家冷白皮大长腿嫩妹,人照9分像,颜值中上,18岁左右,身高170左右,体重90左右,身材匀称苗条高挑,有胸有屁股,天然大b凶圆润饱满挺拔,乳头乳晕小,颜色粉,乳头内陷,敏感,舔几下粉咪咪就会突出来,屁股有肉弹性十足,皮肤白滑嫩,冷白皮,手感佳,全身无纹身,干干净净,大长腿,腰臀比完美,小蝴蝶户型,毛毛少,粉鲍鱼,舔两下就出水,陪洗认真细致,温柔体贴,…
📊 1条车评,综合分 9.2 好评 100% | 人照 10.0 | 服务 9.0 中评 0% | 颜值 9.0 | 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: #张馨予 车牌: @acujs2929727 车费: #8/15 位置: #天府一街 标签: #武侯区 #御姐 #态度车 #颜值车 #自聊 #身材车 #大胸 #大蟒蛇 注: 老师人照和视频一致,频道有很多和客人原相机拍的视频可以参考,本人颜值御姐,颜值很顶,大眼睛高鼻梁,胸是真胸,有d,可以乳交,脂肪胸特别软,手感好,服务不过分都能满足,日起来反馈好完全不怕没感觉,态度也好,情绪价值到位,第一次见面也没有一点陌生感 体验报告汇总 :@chengduainila 上牌或提交报告联系 : @lyihstzw 双向机器人: @Yik…
❤2
📊 1条车评,综合分 8.2 好评 100% | 人照 7.5 | 服务 9.0 中评 0% | 颜值 8.0 | 态度 9.0 差评 0% | 身材 7.5 | 环境 8.0 👆 【点击查看评价】 【成都医科大学认证车库】 花名: #哇塞姐 车牌: @liuwashai 车费: #5/8 位置: #钻石广场 标签: #69 #车震 #包天 #包时 #深喉 #双飞 #舌吻 #上门 #御姐 #服务车 #态度车 #包夜 #成华区 注: 老师身高160,年龄26,体重98,人照分7.5,身材一般,胸b、屁股大,肚子有点赘肉,三点情况,三点褐色,下面紧度适中,毛中等,无异味。老师服务很好,态度认真主动,之前没下过水,基本上姿势都有,还有ab面,毒龙,kiss,69,爱爱反馈真实,作为服务车整体舒服。 体验报告汇总 :@chengduainila 上牌或提交报告联系 : @ly…
📊 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: #婷婷 车牌: @tingting14724 车费: #6/9 位置: #天府二街 标签: #武侯区 #嫩妹 #自聊 #女友感 #颜值车 #冷白皮 注: 妹妹身高不到160 体重80左右,年龄19,人照8分,妹妹属于乖乖女长相,照片略显成熟。身材匀称,真人长相我是相当喜欢,笑起来很乖。腰腹无赘肉 无纹身,腿上有以前骑车摔的疤。冷白皮,B奶又白又挺,这奶子属于可玩年系列,乳头跟男的差不多大 ,逼又粉又嫩,正儿八经三点粉 毛量中等,批紧水多,包裹感相当好,妹妹刚下水啥都不懂,单纯的很。妹妹虽然性经验不多,但是口的相当好,口的时候会包会吸,差点把我吹交代了,只能说妹妹在这…
📊 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: #兔兔 车牌: @uhfj2255 车费: #6/9 位置: #保利锦外小户 标签:#嫩妹 #态度车 #大胸 #长腿 #武侯区 #代聊 #女友感 #靓妹 #胸推 注: 兔兔身高160左右,体重110,大胸非常的饱满,小细腿,大屁股,没有赘肉,身材很均匀,很粉,下面一点都不松,毛很多,没有异味,,胸大 应该是大d ,一点不塌 ,一种心动, 一碰就出水,满满的水,做着非常的光滑, 触感非常好,身材圆润 ,推荐喜欢大胸 ,嫩妹,水多的去 上牌或提交报告联系 : @lyihstzw 双向机器人: @Yike55688_bot 注:好评报告五…
😁1
📊 1条车评,综合分 7.8 好评 100% | 人照 7.0 | 服务 8.0 中评 0% | 颜值 7.0 | 态度 9.0 差评 0% | 身材 8.0 | 环境 8.0 👆 【点击查看评价】 【成都医科大学认证车库】 花名: #小七 车牌: @meiniang699 车费: #6/9 位置: #晋吉南路 标签: #武侯区 #少妇 #代聊 #态度车 #身材车 注:小七老师,26岁 身高1.60 体重110左右 身穿粉色连衣裙, 皮肤白嫩,化淡妆,屁股大。少妇s腰。没有小肚子,胸有C➕。乳头粉嫩,有花生粒大。屁股大。屁股上有两个酒窝哈哈!后入超级有感觉,。后入的姿势让你爽翻天,小bb粉嫩毛很少而且很柔软。紧实,水汪汪的。bb豆豆有点大,一摸一搓一捏,老师就受不了。服务有胸推,舌吻,用口。深喉是特色,超级爽! 体验报告汇总 :@chengduain…
❤1
📊 1条车评,综合分 9.3 好评 100% | 人照 8.0 | 服务 10.0 中评 0% | 颜值 9.0 | 态度 10.0 差评 0% | 身材 10.0 | 环境 9.0 👆 【点击查看评价】 【成都医科大学认证车库】 花名: #温柔玲薇 车牌: @dinasha1 车费: #6/11 位置: #昭觉寺 标签: #成华区 #御姐 #自聊 #态度车 #感觉车 #身材车 #颜值车 注: 玲薇老师,25岁 目测身高1.65左右 体重100 皮肤细腻滑嫩,化淡妆,齐肩黑发,身上无一丝赘肉。胸有C+一手握不住,两只手捧住杠杠的。乳头粉嫩,有黄豆大小。一搓捏立马硬起来了。梨型身材,屁股太有感觉,没有一点点多余的赘肉。后入的姿势让你爽翻天,小bb粉嫩汁多,超级紧实,属于易敏感体质,一摸就水汪汪的。摸了一把,没有一点点异味儿。毛不多不少。 体验报告汇总 …
【成都医科大学认证车库】 花名: #苏瑶 车牌: @aa51132 车费: #4/7 位置: #东升镇 标签: #双流区 #代聊 #态度车 #御姐车 #东升 #4p 注: 年龄26左右,人照相似9,去掉磨皮美白就是本人,身高155/体重48,36d大胸,御姐,身材匀称,皮肤光滑,态度热情,下面褐色小蝴蝶,水超多,包裹感良好,服务态度很好,陪洗很仔细,服务三件套+69+大蟒蛇,爱爱反馈良好各种姿势随意切换,4p性价比极高 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
❤4👍1
🎉🎉🎉 开奖通知 🎉🎉🎉 🎰 💥💥医科大联合初樱嫩妹社给兄弟们送福利啦 ⚠️ 抽奖说明: 1.中奖者三天内兑奖; 2.炸号不予兑奖。 🎅 联系领奖:@wuhbmd 🙋 参与人数:585 中奖名单如下: 1. 奥特曼 奖品:188现金红包 2. 冰淇淋流泪 奖品:128现金红包 3. 黑崎一护 奖品:88现金红包 4. 汉堡🍔 奖品:200优惠劵 5. Tzafrir 奖品:200优惠劵 6. 魏文帝 奖品:200优惠劵 7. 寄驿 奖品:100优惠劵 8. 天气 奖品:100优惠劵 9. 杠上开花 奖品:100优惠劵 10. 我今晚想叼你 奖品:100优惠劵 11. 清风 奖品:100优惠劵 12. 寒梅 奖品:100优惠劵 这次没中,下次一定! 🎁 点击查看更多抽奖
Showing the 12 most recent of 93 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 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.
- First edit seen
- 8 August 2026
- Most recent edit
- 24 August 2026
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 6 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.
@chengduainila · 19,41978 posts成都医科大学修车群
@chengdu338 · 29,43377 posts保安
@abaoan_bot · 97,36259 posts极搜🔍资源搜索@JISOU
@jisou2 · 1,747,9805 posts幸运抽奖导航
@LotteryNavChannel888 · 33,3483 posts成南~初樱嫩妹社🫧
@xiaotxy · 7,7982 posts成都百花半套会所
@CD_baihua · 17,5071 post成都靠谱半套/全套工作室
@chengdubantao398 · 3,5201 post成南~初樱嫩妹社❀
@chuyu52 · 3,3671 post全国包养萝莉/处女/学妹(广告频道)
@cpth6 · 221 post成都夜猫子💕会所交流群💕
@RYDtyub · 5,5081 post成都夜猫子💃半套,全套,安排
@YpDticiq · 8,0251 post
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 17 September 2026 — this entry's latest reading, not the date you are reading this.
“成都医科大学上牌车库” (@shangpailaoshi), 28,834 subscribers as measured 17 September 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.