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Channel

成都医科大学上牌车库

@shangpailaoshi

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

25,395subscribers

+969 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
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 上牌或提交报告联系 : @lyihstzw 双向机器人: @Yike558_bot 商务合作可以联系上面的号
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 live14 August 2026
Measurements held9
Confirmed unchanged1 time, most recently 14 August 2026
On Telegramt.me/shangpailaoshi

Growth

24,42625,39524,910.56 August 2026 — 24,426 subscribers7 August 2026 — 24,601 subscribers8 August 2026 — 24,722 subscribers9 August 2026 — 24,823 subscribers10 August 2026 — 24,913 subscribers11 August 2026 — 24,999 subscribers12 August 2026 — 25,085 subscribers13 August 2026 — 25,192 subscribers14 August 2026 — 25,395 subscribers6 August 202614 August 2026
9 measurements spanning 8 days, net +969. 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 24,281–25,540 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
14 Aug 2026, 16:3625,395+203
13 Aug 2026, 08:3825,192+107
12 Aug 2026, 11:0925,085+86
11 Aug 2026, 07:5124,999+86
10 Aug 2026, 05:4124,913+90
9 Aug 2026, 06:4124,823+101
8 Aug 2026, 08:3124,722+121
7 Aug 2026, 09:2224,601+175
6 Aug 2026, 20:1624,426first reading

Engagement

34 posts held, back to 4 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 22 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
2.80%
avg views ÷ 25,395 subscribers
Avg views / post
711
34 posts measured
Reaction rate
0.17%
reactions ÷ views · ER floor
Posts in window
34
of 34 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 16 of 34 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 15 August 2026
Posts held34 (4 August 202615 August 2026)
Views total24,160
Reactions total21
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken15 Aug 2026, 16:15 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
3,120
Videos
179
Links
590

Lifetime counters from Telegram’s own channel header, read 15 August 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
40s
Average length
10s

Measured directly from 4 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

21 reactions across 13 posts, in 2 distinct kinds. The most used accounts for 85.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
1885.7%
👍314.3%

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 16 of the 34 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 21reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 34 most recent posts we hold, published 4 August 2026 to 15 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.

Recent posts

15 Aug 2026, 13:59 UTC204 viewsread 15 August 2026
Photo

【成都医科大学认证车库】 花名: #玥曦 车牌: @lgngcz121 车费: #6/9 位置: #锦外小户 标签: #武侯区 #少妇 #自聊 #态度车 #微胖 注:老师身高168左右,年龄30左右,体重60左右,人照7分,本人颜值7分,微胖有肚子,胸C较软,乳晕正常乳头小,屁股大,背部大面积纹身,左胸小纹身,左脚踝纹身,这个跟课表完全不符。下面蝴蝶逼,正常毛量,颜色较深,水量不错,紧度一般,叫声自然。老师服务较少,陪浴,亲胸,口,做,做完简单按摩,说有接吻和69。老师比较温柔,有点夹子音,配合度还可以,会的不多说可以学。抽烟但抽的少,没闻到烟味。 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 成都医科大学聊天群:@che

15 Aug 2026, 10:40 UTC297 views1 reactionsread 15 August 2026
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【成都医科大学认证车库】 花名: #小七 车牌: @Xiaoqi1257890 车费: #5/8 位置: #天府三街 标签: #嫩妹车 #态度车 #女友感 #自聊 #舌吻 #邻家妹妹 #武侯区 注: 老师24左右,162cm,46kg,胸又大又白,人照9,颜值耐看,皮肤白滑,蝴蝶逼很紧水多,态度很好,女友感强,配合度好,体验感拉满,开五性价比很高,值得体验。 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 成都医科大学聊天群:@chengdu338 #成都电报 #成都楼凤 #成都修车

1

15 Aug 2026, 10:34 UTC295 viewsread 15 August 2026
Photo

📊 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: #清清 车牌: @qqingmm 车费: #5/8 位置: #东郊记忆 标签: #成华区 #少妇 #代聊 #服务车 #感觉车 #态度车 注: 老师身高160,年龄30往上,体重85,身材人照分9,本人邻家少妇,脸型较好,但脸些许雀斑,感觉化妆会好看些,身材匀称,腿修长手感好,皮肤正常,胸C,底部较硬,乳头两颗花生米大小,微下垂,握感一般,屁股有肉手感好,无赘肉,户型鲍鱼型,颜色偏黑,乳头2个花生米大小,水多,下面微紧,毛比较多,日感反馈自然,无异味。服务陪浴、调情指划,正反面舌滑、舔胸、裸口、舔蛋、吸蛋、臀推、制服、毒龙、做,颜射、口射,情绪价值好,服务态度一流,帮

14 Aug 2026, 16:39 UTC677 views2 reactionsread 15 August 2026
Photo

📊 1条车评,综合分 8.8 好评 100% | 人照 9.0 | 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: #沈清梨 车牌: @qingli520520 车费: #6/9 位置: #天府二街 标签: #武侯区 #御姐 #自聊 #女友感 #身材车 #颜值车 #大蟒蛇 注: 沈妹妹,年龄23,本人颜值挺高,皮肤比较白,摸起来光滑,身高165左右,体重90多斤,身材高挑,手臂有纹身,天然胸C,乳头较小颜色粉,户型小蝴蝶颜色浅粉,比较紧水也多。屁股翘日起来比较爽。服务鸳鸯浴,舔奶头,舔蛋,69,主动大蟒蛇,态度也很好,女友感比较强,爱爱反馈真实,各种姿势配合到位,情绪价值拉满。六米御姐天花板,非常值得推荐! 体验报告汇总 :@chengduaini

2

14 Aug 2026, 16:25 UTC342 viewsread 15 August 2026
Photo

📊 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: #丽娜 车牌: @CDLina999 车费: #6/10 位置: #东郊记忆 标签: #成华区 #洋马 #御姐 #代聊 #态度车 #服务车 注: 妹妹是泰国混血儿,身高162左右,年龄25岁,体重48公斤,人照有点小差别,人照打分8分。妹妹身材匀称,无赘肉。皮肤属于小麦色,但是很光滑,mi咪B+,乳头小,手感很好。人工白虎,下面湿度正常,紧度较紧。妹妹水中萧很有特点,反复用热水,凉水刺激弟弟。洗澡特别仔细,弟弟被清洗三遍。虽然只能简单英语交流,但是全程服务态度很好,特别是还将我的衣服裤子折叠后放好,很贴心。 体验报告汇总 :@chengduainila 上牌或提

14 Aug 2026, 16:24 UTC315 viewsread 15 August 2026
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【成都医科大学认证车库】 花名: #王语嫣 车牌: @wwwyu998 车费: #7/12 位置: #东光 标签: #锦江区 #东光 #御姐 #自聊 #服务车 #气质车 #眼镜 注: 老师身高165,年龄28,体重49kg,人照分8.8,本人兼具少妇和御姐气质,戴上眼镜,气质更加,身材匀称,无赘肉,小肚子有些许褶皱,双腿修长,皮肤白皙,胸B+到C微硬不影响手感,乳头花生米大小,颜色粉褐,不下垂,有握感,屁股有肉紧致手感好,户型鲍鱼型,颜色偏粉褐,出水正常,无异味,下面较紧,毛量正常,日感反馈自然。服务莞式一条龙,服务会调动情绪,像漫游,舔耳,口,技术一流并且时长足够,帮忙擦干,无机车,会聊天,不尴尬,姿势配合,后入日感非常棒,喜欢御姐服务的兄弟可以体验出击。 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

14 Aug 2026, 12:43 UTC450 viewsread 15 August 2026
Video

欢迎来到四川|成都.Chengdu 成都Kiss极致严选外围 う全国Bao养う全国商Kう全半会所 因为专注|所以专业 专注成都八年只为一件性福的事 Kiss三星服务|省心|放心|开心 更多资源|更多活动|更多反馈 让您出击不踩坑 永久Id 🔤🔤🔤🔤6️⃣6️⃣6️⃣

13 Aug 2026, 07:16 UTC927 viewsread 15 August 2026
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📊 1条车评,综合分 8.5 好评 100% | 人照 8.0 | 服务 10.0 中评 0% | 颜值 8.0 | 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: #小溪 车牌: @Xiaox998 车费: #5/8 位置: #天府五街 标签: #武侯区 #少妇 #自聊 #服务车 #毒龙 注: 妹妹年龄25左右,身高162,体重52公斤,人照8.5分。妹妹mi咪C罩杯,形态挺拔,手感很好,下面毛量较多,湿润,外褐内粉。肚子和大腿有少量赘肉。妹妹最大特色是服务内容,非常巴适地道,过程很舒服,包括鸳鸯浴,毒龙,波推,阴推等等,技术一流,值得去体验。妹妹态度较好全程无机车行为。 体验报告汇总 :@chengduainila 上牌或提交报告联系 : @lyihstzw 双向机器人: @Yike

12 Aug 2026, 09:41 UTC930 viewsread 14 August 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

12 Aug 2026, 09:41 UTC936 views1 reactionsread 14 August 2026
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📊 1条车评,综合分 8.0 好评 100% | 人照 8.0 | 服务 7.0 中评 0% | 颜值 8.0 | 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: #Mikey 车牌: @CDMikey9 车费: #6/9 位置: 东郊记忆 标签: #成华区 #态度车 #代聊 #感觉车 #身材车 #洋马 注: 老师门后迎接 ,身高158,年龄28左右吧,体重95,人照分8,老师身材不错 没有赘肉,,腿、胸c褐色、屁股又大又圆,服务态度很好 不过服务较少,陪洗很仔细,上床舔了吹,让后就带套开干,下面紧度正常,毛不多,泰妹交流全靠意会和简单英语,走时老师毕恭毕敬站着等穿好衣服送你 推荐打卡 体验报告汇总 :@chengduainila 上牌或提交报告联系 : @lyihstzw 双向机器人

1

12 Aug 2026, 06:07 UTC850 views1 reactionsread 14 August 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: #掌中宝 车牌: @zhangzbao 车费: #4/7 位置: #郫县红光 标签: #郫都区 #代聊 #坦克 #泻火 #嫩妹 注:坦克车,但是胸是真大,颜值偏幼女型,喜欢这款的可以上,定价400也是有道理的,不要有太大的期待,就当纯卸火车开,口活不错,这点值得推荐,缺点是服务项目不多,毕竟比较年轻,很多都不会也正常,有很大的待开发空间,值得好好教一下。老师有抽烟,介意的大哥可以避开,总结一下,就是喜欢耍胸的可以去。其他就不要有太大的期待了。 体验报告汇总 :@chengduainila 上牌或提交报告联系 : @lyihstzw 双向机器人: @Yike

1

12 Aug 2026, 05:34 UTC805 viewsread 14 August 2026
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📊 1条车评,综合分 8.5 好评 100% | 人照 9.0 | 服务 7.0 中评 0% | 颜值 9.0 | 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: #茉莉 车牌: @moolillll 车费: #7/12 位置: #东郊记忆 标签: #嫩妹车 #态度车 #颜值车 #代聊 #舌吻 #邻家妹妹 #成华区 注: 老师年龄19岁,163,90斤,无纹身,皮肤手感嫩滑,肤色白皙,人照9分;颜值不错,胸为天然b,白嫩好rua,下面户型为小蝴蝶,颜色外褐内粉,周围毛量较多,服务有点少不过也正常,三件套,69,大蟒蛇,陪洗 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

Showing the 12 most recent of 34 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 2 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
9 August 2026

Citation-graph rank

Citation-graph rank — 250,804 of 1,480,944entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

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 5 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 14 August 2026 — this entry's latest reading, not the date you are reading this.

“成都医科大学上牌车库” (@shangpailaoshi), 25,395 subscribers as measured 14 August 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.