Telegram RegisterThe public register of Telegram

Channel

成都星辰车库s3(开课专用)

@xinvchenbg

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

4,816subscribers

-62 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1002344871468
TypeChannel
Username@xinvchenbg
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live13 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/xinvchenbg

Topic

Adult — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 83% 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.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear word for word on 1 other registered channel. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (5 of the pairs behind the counts below)
Posted firstThenOverlapGap
@cdxcxrcku/39146 Aug 2026, 13:50 UTC@xinvchenbg/4340 · this entry6 Aug 2026, 13:52 UTC1.002 minutes
@cdxcxrcku/39176 Aug 2026, 14:10 UTC@xinvchenbg/4342 · this entry6 Aug 2026, 14:11 UTC1.00under a minute
@xinvchenbg/4346 · this entry6 Aug 2026, 16:22 UTC@cdxcxrcku/39216 Aug 2026, 16:22 UTC1.00under a minute
@xinvchenbg/4350 · this entry7 Aug 2026, 02:57 UTC@cdxcxrcku/39277 Aug 2026, 02:57 UTC1.00under a minute
@cdxcxrcku/39287 Aug 2026, 11:48 UTC@xinvchenbg/4351 · this entry7 Aug 2026, 11:49 UTC0.9572 seconds
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@cdxcxrcku5 (5/5 hand-verifiable sample passed)0.99under a minute@cdxcxrcku (41)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 4 of the 4 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.

“Published first” means first in this corpus. We hold 7 comparable posts for this entry, running 6 August 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Across the whole group of 2, the earliest publisher we hold is @cdxcxrcku. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_copy, last confirmed 7 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Also posting the same content

This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.

Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

4,8164,8784,8477 August 2026 — 4,878 subscribers7 August 2026 — 4,878 subscribers10 August 2026 — 4,824 subscribers13 August 2026 — 4,816 subscribers7 August 202613 August 2026
4 measurements spanning 6 days, net -62. 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 4,807–4,887 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 14:384,816-8
10 Aug 2026, 08:034,824-54
7 Aug 2026, 12:484,878no change
7 Aug 2026, 12:374,878first reading

Engagement

15 posts held, back to 6 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 8 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
2.71%
avg views ÷ 4,816 subscribers
Avg views / post
131
15 posts measured
Reaction rate
0.275%
reactions ÷ views · ER floor
Posts in window
15
of 15 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 2 of 15 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 11 August 2026
Posts held15 (6 August 202611 August 2026)
Views total1,961
Reactions total1
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 05:15 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

Video runtime
23s
Average length
8s

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.

Reaction mix

1 reaction across 1 post, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
1100.0%

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 2 of the 15 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 1reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 15 most recent posts we hold, published 6 August 2026 to 11 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

11 Aug 2026, 08:21 UTC98 viewsread 12 August 2026
Video

💎红楼阁——高端会所💎 🌟主营-95半套-98全套-98海选 ❤️高端全套大海选 一排一排的选 氛围感拉满 选满意在玩【质量相当于有外围中圈和中大圈】 ✅自家高端95半套店 不冲卡 单次消费 没有隐形消费 高质量 服务有保障 每天在线30➕选满意在消费 有免费小吃 泡澡 凌晨后可留宿 ❤️全城也可以给你安排 高端95半套-98全套 会所宗旨:诚信经营服务至上、让你乘兴而来满意而归 📣狼友评价:@BBmOGY9 📛🫠🫠🫠:@BmOGY9 📛😪🫠🤗:@MBmOGY9 ☎️ : 19280903022 🪨 : ccvip2026 ✈️ : @aofeng567 🤖 : @CDHonglou_bot 😀😃😄😆

11 Aug 2026, 04:34 UTC127 viewsread 12 August 2026
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📊 1条车评 写报告 好评 100% 中评 0% 差评 0% 成都星辰楼凤修车车库 【编号】 #XC925 【花名】 #艺涵 【车牌】 @sylail 【地址】 #昭觉寺 【标签】 #成都 #成都修车 #成都楼凤 #成华区#bbw 【硬件】身高165cm,体重130+斤,胸d,年纪24岁,人工白虎,一线天水多,紧,包裹感强 (无纹身)。 【软件👏👏】鸳鸯浴,🐍吻,无套吹箫,深喉,舔批,爱爱。 【课费】600/50 900/90 #6/9 【优惠】无 【验证】 报告 1 2 3 4 5 6 【综合评分】:态度/服务: 8分 颜值: 7.5,身材:7,综合: 7.5分。 【新人锐评】(字数相当,不能比样板少) (含优点和瑕疵) 优点: 人照是本人,修图比较厉害,老师很爱卫生,服务前会洗的很干净,自备漱口水,安全又卫生,大屁股,皮肤白皙,全身无纹身,手感嫩滑,人工白虎,一线天,水多,轻轻摸

11 Aug 2026, 04:06 UTC108 viewsread 12 August 2026
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📊 2条车评 写报告 好评 100% 中评 0% 差评 0% 成都星辰楼凤修车车库 【编号】 #XC857 【花名】 #小宝 【车牌】 @eggdc15 【地址】 #东郊记忆 【标签】 #成都 #成都修车 #成都楼凤 #成华区 #御姐车 #态度车 #大奶 #符文 #代聊 #6P 【硬件】身高160cm,体重105斤,胸D,年纪24岁,正常肤色有点干,身上纹身稍多,人工白虎水多较紧日感好毛多。 【软件👏👏】乳胶,制服,浅蛇,无套吹箫,舔批,爱爱。 【课费】600/50 1000/90 #6/10 (VIP可半价) 【优惠】无 【验证】 报告 1 2 3 4 5 6 【综合评分】:软件: 8.5分 硬件: 8.5分 ,综合: 8.5分。 【新人锐评】(字数相当,不能比样板少) (含优点和瑕疵) 优点: 异域风情御姐,人照相符,态度不错聊天不冷场,天然大D手感好,人工白虎剃的干净,水多包裹

11 Aug 2026, 02:46 UTC120 viewsread 12 August 2026
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📊 0条车评 写报告 好评 0% 中评 0% 差评 0% 成都星辰楼凤修车车库 【编号】 #XC924 【花名】 #小卢 【车牌】 @xxl8989 【地址】 #省骨科医院 【标签】 #成都 #成都修车 #成都楼凤 #武侯区 #嫩妹车 #态度车 #大长腿 #蛇蛇精 #身材车 #排骨精 #女友感 #代聊 #8P #颜值车 【硬件】身高172cm,体重94斤,胸B,年纪19岁,皮肤偏黄黑无纹身,馒头逼,毛量少,水多很紧。 【软件👏👏】鸳鸯浴,🐍吻,无套吹箫,深喉,舔批,爱爱。 【课费】800/50 1300/90 #8/13 (VIP可半价) 【优惠】无 【验证】 报告 1 2 3 4 5 6 【综合评分】:态度/服务: 8.8分 颜值: 9.0,身材:8.8 ,综合: 8.8分。 【新人锐评】(字数相当,不能比样板少) (含优点和瑕疵) 优点: 颜值嫩妹,人照相符,极致排

11 Aug 2026, 02:42 UTC121 viewsread 12 August 2026
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成都星辰楼凤修车车库 【编号】 #XC923 【花名】 #南湘 【车牌】 @NX2002a 【地址】 #高升桥 【标签】 #成都 #成都修车 #成都楼凤 #武侯区 #御姐车 #颜值车 #态度车 #大长腿 #身材车 #冷白皮 #颜值车 #一线天馒头逼 【硬件】身高170cm,体重88斤,胸C-,年纪26岁,冷白皮,一线天馒头,毛多,紧,包裹感强。 【软件👏👏】鸳鸯浴,无套吹箫,漫游,毒🐉,👅胸,👅🥚,爱爱。 【课费】900/60 1400/90 #9/14 (VIP可半价) 【优惠】无 【验证】 报告 1 2 3 4 5 6 【综合评分】:态度/服务: 9.5分 颜值: 9.6,身材:9.5,综合: 9.6分。 【新人锐评】(字数相当,不能比样板少) (含优点和瑕疵) 优点: 颜值御姐,人照相符,极品身材,细腰翘臀,浑身无赘肉,大长腿,皮肤白皙,手感纵享丝滑、白皙紧致,胸C-手感好,乳头小,态度好,服务好

11 Aug 2026, 02:08 UTC127 viewsread 12 August 2026
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📊 0条车评 写报告 好评 0% 中评 0% 差评 0% 成都星辰楼凤修车车库 【编号】 #XC922 【花名】 #维C 【车牌】 工兵未接完 【地址】 #大天路 【标签】 #成都 #成都修车 #成都楼凤 #成华区#嫩妹#态度车#颜值车 【硬件】18岁妹妹。身高163cm,体重100斤,小麦色肤色。胸B+柔软圆润。胸部附近有些胎记。蝴蝶逼逼,外褐里粉,又紧又湿。 【软件👏👏】洗,口,啪啪,浅吻,炫逼,亲胸 【课费】600/50 1200/90 #6/12 (VIP可半价) 【优惠】无 【验证】 报告 1 2 3 4 5 6 【综合评分】:态度/服务: 9分 颜值: 9,身材:9 ,综合: 9分。 【新人锐评】(字数相当,不能比样板少) (含优点和瑕疵) 优点: 颜值嫩妹,人照相符,身材匀称微微胖。态度和性格很好,全场不冷场。听话配合。 瑕疵: 胸部附近有些胎记 同价格

8 Aug 2026, 13:18 UTC79 viewsread 9 August 2026
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成都星辰楼凤修车车库 【编号】 #XC920 【花名】 #小财宝 【车牌】 @CDcaibao 【地址】 #东郊 【标签】 #成都 #成都修车 #成都楼凤 #成华区#态度车 #大长腿 #bbw #颜值车 #服务车#大胸#嫩妹 【硬件】身高160cm,体重110斤,小腹平坦, 【软件👏👏】三件套 爱爱🐍 【课费】#5 (VIP可半价) 【优惠】无 【验证】 报告 1 2 3 4 5 6 【综合评分】:软件: 8分 硬件: 8.3.分 ,综合: 8.3分。 【新人锐评】 (含优点和瑕疵) 优点: 嫩妹 活泼 喜欢聊天 瑕疵: 服务偏少 同价格对比:开5合适 总结:(200字左右) 老师相处氛很好很自然,会聊天。下面紧,大屁股 适合狼友类型: 适合喜欢身材控,bbw 【评价者】: @ccd 【折扣】:#星辰VIP会员上课最低5折, 报告:@cdxcbg1 聊天大群:@cdxcclub 投诉、上牌联系

8 Aug 2026, 01:37 UTC140 viewsread 9 August 2026
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📊 1条车评 写报告 好评 100% 中评 0% 差评 0% 成都星辰楼凤修车车库 【编号】 #XC919 【花名】 #亦可可 【车牌】 @kekemeizi 【地址】 #东郊记忆 【标签】 #成都 #成都修车 #成都楼凤 #成华区 #人照相符 #代聊 #御少车 #态度车 #身材车 #服务车 #逗比 #女友感 #颜值车 #一线天逼 #6/9 【硬件】身高160cm,体重90多斤,胸C,年纪25岁左右,皮肤嫩滑紧致,一线天逼,毛少,紧度一般,水多, 有纹身。 【软件👏👏】鸳鸯浴,kiss,过水,吸皮,口莎,胸推,臀推,阴推,无套吹箫,深喉,舔批,爱爱。 【课费】600/60 900/90 #6/9 (VIP可半价) 【优惠】无 【验证】 【综合评分】:态度/服务: 9分 颜值: 9.分,身材: 8.5,综合: 9分。 【新人锐评】 优点: 颜值御少,人照相符,细腰大屁股,腰部无赘肉,

8 Aug 2026, 01:22 UTC126 viewsread 9 August 2026
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成都星辰楼凤修车车库 【编号】 #XC918 【花名】 #泰妹Zara 【车牌】 @cdzara6 【地址】 #东郊记忆 【标签】 #成都 #成都修车 #成都楼凤 #成华区 #少妇车 #态度车 #蛇蛇精 #泰妹 【硬件】身高155cm,体重90斤,胸B,年纪27岁,白虎,懵醉仙逼,紧,包裹感强 (无纹身)。 【软件👏👏】鸳鸯浴,🐍吻,无套吹箫,深喉,舔批,爱爱。 【课费】500/50 900/90 #5/9 (VIP可半价) 【优惠】无 【验证】 【综合评分】:态度/服务: 9.8分 颜值: 7.5,身材:8,综合: 9分。 【新人锐评】 优点: 泰国少妇,AI照片,不会中文,可以英语交流,身材不能说很瘦,也不能说胖,腰部无太多赘肉,皮肤手感嫩滑紧致Q弹,胸B手感好,乳头深褐色,态度好,服务好,🐍吻真实自然,口活厉害,舌头会在鸡鸡上跳舞,懵醉仙逼,白虎,舔批无异味,批小很紧,包裹感极强,阴道很浅,日感爽翻天

7 Aug 2026, 11:49 UTC158 views0 reactionsread 9 August 2026
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📊 1条车评 写报告 好评 100% 中评 0% 差评 0% 成都星辰楼凤修车车库 【编号】 #XC917 【花名】 #如忆 【车牌】 @ruyi86666 【地址】 #理工大学 【标签】 #成都 #成都修车 #成都楼凤 #成华区 #嫩妹车 #态度车 #蛇蛇精 #身材车 #女友感 #颜值车 #良家感 #微胖 #BBW 【硬件】身高168cm,体重约57Kg,胸天然C+,大屁股,20岁,毛量不多,水多紧润,包裹感佳 ,小手臂有点纹身。 【软件👏👏】共浴、调情、🐍吻、舔胸、无套吹箫,爱爱。 【课费】600/50 1000/90 #6/10 (VIP可半价) 【优惠】无 【验证】 报告 1 2 3 4 5 6 【综合评分】:态度/服务: 9分 颜值: 8,身材:8,综合: 8.3分。 【新人锐评】(字数相当,不能比样板少) (含优点和瑕疵) 优点:嫩妹,刚下水,没有什么风尘味,长的很

6 Aug 2026, 16:22 UTC206 views1 reactionsread 9 August 2026
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📊 1条车评 写报告 好评 100% 中评 0% 差评 0% 成都星辰楼凤修车车库 【编号】 #XC916 【花名】 #小蛋挞 【车牌】 @wacxdt 【地址】 #成渝立交 【标签】 #成都 #成都修车 #成都楼凤 #锦江区 #嫩妹车 #态度车 #大长腿 #蛇蛇精 #身材车 #排骨精 #女友感 #萝莉 #冷白皮 #邻家妹子 #女儿感 #筷子腿 #情绪价值 【硬件】身高165cm,体重90斤,天然小b凶,年纪18岁,冷白皮,紧,水多,昆感佳,锁骨有一处小纹身,好看 【软件👏👏】鸳鸯浴,🐍吻,无套吹箫,舔批,爱爱。 【课费】600/50 1000/90 #6/10 (VIP可半价) 【优惠】无 【验证】 报告 1 2 3 4 5 6 【综合评分】:态度/服务: 9分 颜值: 9,身材:9 ,综合: 9分。 【新人锐评】(字数相当,不能比样板少) (含优点和瑕疵) 优点: 邻家感颜值嫩

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6 Aug 2026, 14:11 UTC163 viewsread 8 August 2026
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成都星辰楼凤修车车库 【编号】 #XC915 【花名】 #格格 【车牌】 @gege13142 【地址】 #桐梓林 【标签】 #成都 #成都修车 #成都楼凤 #武侯区 #御姐车 #态度车 #大长腿 #身材车 #御姐 #颜值车 #邻家姐姐 #新疆异域风情 #眼神莎 【硬件】身高约168cm,体重86斤,胸B,年纪约28岁左右,毛正常,紧正常,包裹感强 (无纹身)。 【软件👏👏】 基础按摩,臀莎、指莎、匈莎、无套吹箫,深喉,舔🥚,AA、毒🐲 【课费】700p/50 1000pp/80 #7p/10pp (VIP可半价) 【优惠】无 【验证】 报告 1 2 3 4 5 6 【综合评分】:态度/服务: 8.5分 颜值: 8.5,身材:8.5 ,综合: 8.5分。 【新人锐评】 优点: 颜值韵味御姐,祛美白美颜人照相符合,细腰臀浪,腰部无赘肉,大长腿,皮肤白皙,手感嫩、滑、紧致Q弹,胸B手感好、软,乳头葡萄

Showing the 12 most recent of 15 posts we hold for @xinvchenbg. 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.

Citation-graph rank

Citation-graph rank — 793,016 of 1,345,403entries 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 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.

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

“成都星辰车库s3(开课专用)” (@xinvchenbg), 4,816 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/xinvchenbg.

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.