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Channel

成都•疯狂女儿国后宫🔞

@nverguogk

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

47,854subscribers

+2,762 since we began measuring on 24 August 2026

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

Register entry

Telegram ID-1002418771755
TypeChannel
Username@nverguogk
Description主群:https://t.me/CD_NRGXC 如遇IOS限制可私聊 :@Renhao_NRG 备用群车库通用:@cdnrgby (如无法解除可在备用群搜索)
CreatedBetween 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded24 August 2026
Last confirmed live14 September 2026
Measurements held16
Confirmed unchanged1 time, most recently 14 September 2026
On Telegramt.me/nverguogk

Topic

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 9 September 2026 and assigned it the closest of 31 fixed categories, at 81% 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

45,09247,85446,47324 August 2026 — 45,092 subscribers25 August 2026 — 45,186 subscribers26 August 2026 — 45,192 subscribers27 August 2026 — 45,442 subscribers28 August 2026 — 45,498 subscribers29 August 2026 — 45,696 subscribers30 August 2026 — 45,880 subscribers31 August 2026 — 46,022 subscribers1 September 2026 — 46,187 subscribers2 September 2026 — 46,291 subscribers3 September 2026 — 46,218 subscribers5 September 2026 — 46,481 subscribers8 September 2026 — 46,929 subscribers11 September 2026 — 47,429 subscribers13 September 2026 — 47,598 subscribers14 September 2026 — 47,854 subscribers24 August 202614 September 2026
16 measurements spanning 21 days, net +2,762. 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 44,678–48,268 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
14 Sept 2026, 19:5947,854+256
13 Sept 2026, 08:1647,598+169
11 Sept 2026, 10:3847,429+500
8 Sept 2026, 15:2146,929+448
5 Sept 2026, 09:5746,481+263
3 Sept 2026, 12:4046,218-73
2 Sept 2026, 04:2546,291+104
1 Sept 2026, 01:0846,187+165
31 Aug 2026, 02:3446,022+142
30 Aug 2026, 05:0345,880+184
29 Aug 2026, 07:5545,696+198
28 Aug 2026, 05:2545,498+56
27 Aug 2026, 05:1745,442+250
26 Aug 2026, 04:0245,192+6
25 Aug 2026, 03:5845,186+94
24 Aug 2026, 18:3045,092first reading

Engagement

49 posts held, back to 21 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 46 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
3.06%
avg views ÷ 47,854 subscribers
Avg views / post
1,470
49 posts measured
Reaction rate
0.113%
reactions ÷ views · ER floor
Posts in window
49
of 49 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 36 of 49 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 September 2026
Posts held49 (21 August 202615 September 2026)
Views total71,830
Reactions total66
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken16 Sept 2026, 03:32 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
3,090
Videos
295
Links
675

Lifetime counters from Telegram’s own channel header, read 16 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 48s
Average length
9s

Measured directly from 19 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 30 posts, in 2 distinct kinds. The most used accounts for 97.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
6497.0%
👎23.03%

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 36 of the 49 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 49 most recent posts we hold, published 21 August 2026 to 15 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

15 Sept 2026, 03:56 UTC≈1,080 views2 reactionsread 16 September 2026
Photo

成都修车 #成都楼凤 #成都 📊1条车评,综合评分8.3 好评 0% |人照 8.2 |服务 8.1 中评 100% |颜值 8.3 |态度 8.5 差评 0% |身材 8.2 |环境 8.5 ⚠️⚠️无论新旧老师,差评过多直接下牌 给老师写评价:https://t.me/NEGhg_bot?start=commentTeacher-TE178944459657 年龄: 26 身高: 165 体重: 60 罩杯: H 联系老师: @yangguifei88 双向联系老师: 点击联系杨贵妃 ⚠️⚠️【花名】 #成都第一大奶航母杨贵妃 【地址】 #成华区 【标签】 #少妇/ #服务车/ #自聊/#成华区/ 【车牌】@yangguifei88 【硬件】年龄26 身高165 体重60kg 罩杯h 肤色正常 无纹身 下面户型馒头 毛量正常

2

Signed 女儿国后宫总管

15 Sept 2026, 03:47 UTC≈1,210 views1 reactionsread 16 September 2026
Photo

成都修车 #成都楼凤 #成都 📊1条车评,综合评分7.67 好评 0% |人照 8 |服务 7 中评 100% |颜值 7 |态度 9 差评 0% |身材 8 |环境 7 ⚠️⚠️无论新旧老师,差评过多直接下牌 给老师写评价:https://t.me/NEGhg_bot?start=commentTeacher-TE178944406140 年龄: 18 身高: 160 体重: 45 罩杯: B 联系老师: @nnsjsjee 双向联系老师: 点击联系兔兔 【花名】 #兔兔 【地址】 #高新区 #天府三街 【标签】 #嫩妹 #态度车 #大蟒蛇 #代聊 #天府三街 #上门 #洛丽塔 【车牌】@nnsjsjee 【硬件】18岁 160左右 体重90 胸型馒头饱满B+ 肤色小麦 无纹身 户型蝴蝶 少量毛 前戏就很湿,很紧,洞口小。人照妆

1

Signed 女儿国后宫总管

15 Sept 2026, 03:45 UTC828 views2 reactionsread 16 September 2026
Photo

成都修车 #成都楼凤 #成都 📊0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 ⚠️⚠️无论新旧老师,差评过多直接下牌 给老师写评价:https://t.me/NEGhg_bot?start=commentTeacher-TE178944390475 年龄: 29 身高: 165 体重: 55 罩杯: C 联系老师: @JK777788 双向联系老师: 点击联系温婉 【花名】 #温婉 【地址】 #成华区 【标签】 #御姐 #代聊 #成华区 #服务车 (以上是必有标签,其余标签自由发挥) 【车牌】 @JK777788 【硬件】年龄 29 岁左右 身高 165 体重 55KG 罩杯 C 正常肤色 无纹身 小蝴蝶 人照 8分 【软件】 舔胸,口,做 【课

2

Signed 女儿国后宫总管

13 Sept 2026, 15:38 UTC≈1,840 views3 reactionsread 16 September 2026
Photo

成都修车 #成都楼凤 #成都 📊0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 ⚠️⚠️无论新旧老师,差评过多直接下牌 给老师写评价:https://t.me/NEGhg_bot?start=commentTeacher-TE178931393608 年龄: 30 身高: 170 体重: 55 罩杯: C 联系老师: @euey24 双向联系老师: 点击联系娜娜 【花名】 #娜娜 【地址】 #青羊区 【标签】 #少妇 #代聊 #青羊区 #身材车 #服务车 #大长腿 (以上是必有标签,其余标签自由发挥) 【车牌】 @euey24 【硬件】年龄 30岁左右 身高 170 体重 55KG 罩杯 C (科技) 正常肤色 腿部有纹身 小蝴蝶 毛量较多 身材匀称 【软件】 陪洗、漫游、毒龙

3

Signed 女儿国后宫总管

13 Sept 2026, 15:07 UTC≈1,320 views2 reactionsread 15 September 2026
Photo

成都修车 #成都楼凤 #成都 📊1条车评,综合评分8.5 好评 0% |人照 8 |服务 9 中评 100% |颜值 8 |态度 9 差评 0% |身材 8 |环境 9 ⚠️⚠️无论新旧老师,差评过多直接下牌 给老师写评价:https://t.me/NEGhg_bot?start=commentTeacher-TE178931202109 年龄: 26 身高: 162 体重: 57 罩杯: D 联系老师: @mimianqu 双向联系老师: 点击联系咪咪 【花名】 #咪咪 【地址】 #武侯区 【标签】 #少妇 #服务车 #代聊 #衣冠庙 #大D #态度车 #敏感车 【车牌】@mimianqu 【硬件】年龄26 身高162 体重115 罩杯D 肤色白皙 无纹身 下面户型蝴蝶 毛量正常 湿度大 紧度正常

2

Signed 女儿国后宫总管

13 Sept 2026, 08:26 UTC≈1,300 views2 reactionsread 15 September 2026
Photo

成都修车 #成都楼凤 #成都 📊1条车评,综合评分8.83 好评 100% |人照 9 |服务 8.5 中评 0% |颜值 9 |态度 9 差评 0% |身材 8.5 |环境 9 ⚠️⚠️无论新旧老师,差评过多直接下牌 给老师写评价:https://t.me/NEGhg_bot?start=commentTeacher-TE178928799631 年龄: 23 身高: 159 体重: 40 罩杯: B 联系老师: @CDmumu1 双向联系老师: 点击联系目目 【花名】 #目目 【地址】 #武侯区 桐梓林 【标签】 #御姐 #人照相符 #代聊 #颜值车 #身材车 #态度车 #良家感 #🐍吻 #粉嫩蝴蝶逼 #冷白皮 #6/10 【车牌】@CDmumu1 【硬件】年龄23左右 身高159 体重80多斤 罩杯B 肤色冷白皮 无纹身

2

Signed 女儿国后宫总管

12 Sept 2026, 15:40 UTC≈1,470 views1 reactionsread 15 September 2026
Photo

成都修车 #成都楼凤 #成都 📊1条车评,综合评分8.83 好评 100% |人照 9 |服务 8.5 中评 0% |颜值 9 |态度 9 差评 0% |身材 8.5 |环境 9 ⚠️⚠️无论新旧老师,差评过多直接下牌 给老师写评价:https://t.me/NEGhg_bot?start=commentTeacher-TE178922761488 年龄: 19 身高: 155 体重: 45 罩杯: A 联系老师: @yy070788 双向联系老师: 点击联系悠悠 【花名】 #悠悠 【地址】 #成华区(所在大区) 【标签】 #嫩妹 #颜值车 #敏感车 #代聊 #大观 【车牌】@yy070788 【硬件】年龄 19 身高155 体重 45kg 罩杯 A 竹笋胸 肤色白嫩 无纹身 下面户型 毛量 较少 湿度 紧度 人照相似本人更乖巧 (以上为必填测评选项)

1

Signed 女儿国后宫总管

12 Sept 2026, 14:05 UTC928 views0 reactionsread 13 September 2026
Photo

成都修车 #成都楼凤 #成都 📊0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 ⚠️⚠️无论新旧老师,差评过多直接下牌 给老师写评价:https://t.me/NEGhg_bot?start=commentTeacher-TE178922194323 年龄: 18 身高: 158 体重: 55 罩杯: C 联系老师: @VIP_yiduo2 双向联系老师: 点击联系琪琪 【花名】 #琪琪 【地址】 #武侯区 【标签】 #嫩妹 #代聊 #武侯区 #颜值车 #朗诗熙华府 (以上是必有标签,其余标签自由发挥) 【车牌】 @VIP_yiduo2 【硬件】年龄 18 岁身高 158 体重 55KG 罩杯 C 正常肤色 腿部有纹身 小蝴蝶 毛量较多 微胖 有小肚子人照 8分 【软件】 三件

Signed 女儿国后宫总管

12 Sept 2026, 14:00 UTC844 views0 reactionsread 13 September 2026
Photo

成都修车 #成都楼凤 #成都 📊1条车评,综合评分9.08 好评 100% |人照 9 |服务 9 中评 0% |颜值 9 |态度 10 差评 0% |身材 8.5 |环境 9 ⚠️⚠️无论新旧老师,差评过多直接下牌 给老师写评价:https://t.me/NEGhg_bot?start=commentTeacher-TE178922160375 年龄: 23 身高: 170 体重: 57 罩杯: C 联系老师: @lgngcz121 双向联系老师: 点击联系玥曦 【花名】 #玥曦 【地址】 #武侯区 石羊立交 【标签】 #御姐 #代聊 【车牌】@lgngcz121 【硬件】年龄23 身高170 体重115 罩杯C+ 肤色冷白皮 有纹身 下面户型蝴蝶逼 毛量不多 湿度很湿 紧度很紧 人照相似9分 【软件】

Signed 女儿国后宫总管

12 Sept 2026, 04:42 UTC884 views2 reactionsread 13 September 2026
Photo

成都修车 #成都楼凤 #成都 📊1条车评,综合评分8.25 好评 0% |人照 8 |服务 8.5 中评 100% |颜值 8 |态度 8 差评 0% |身材 9 |环境 8 ⚠️⚠️无论新旧老师,差评过多直接下牌 给老师写评价:https://t.me/NEGhg_bot?start=commentTeacher-TE178918813824 年龄: 30 身高: 162 体重: 47 罩杯: B 联系老师: @qshui896 双向联系老师: 点击联系秋水 【花名】 #秋水 【地址】 #高新区 【标签】 #少妇 #服务车 #自聊 #天府三街 【车牌】@qshui896 【硬件】 年龄 30左右 身高 162 体重 95 罩杯 b+ 肤色 正常肤色 有无纹身 三处纹身 下面户型 小蝴蝶 毛量 少量毛 湿度 很湿 紧

2

Signed 女儿国后宫总管

11 Sept 2026, 17:54 UTC873 viewsread 12 September 2026
Photo

成都修车 #成都楼凤 #成都 📊0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 ⚠️⚠️无论新旧老师,差评过多直接下牌 给老师写评价:https://t.me/NEGhg_bot?start=commentTeacher-TE178914927723 年龄: 25 身高: 165 体重: 47 罩杯: C 联系老师: @nana51 双向联系老师: 点击联系娜娜 【花名】 #娜娜 【地址】 #龙泉驿区 【标签】 #少妇 #身材车 #代聊 #7p #皮肤白皙 #龙泉驿区 #东安湖 【车牌】@nana51 【硬件】年龄25,身高165,体重95,罩杯C,肤色白皙,无纹身,下面户型蝴蝶逼,湿度一般,紧度适中,人照相似8分,照片不是本人,但是本人长相在线,比较有气质 【软件

Signed 女儿国后宫总管

11 Sept 2026, 17:51 UTC772 viewsread 12 September 2026
Photo

成都修车 #成都楼凤 #成都 📊0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 ⚠️⚠️无论新旧老师,差评过多直接下牌 给老师写评价:https://t.me/NEGhg_bot?start=commentTeacher-TE178914907283 年龄: 30 身高: 160 体重: 50 罩杯: C 联系老师: @LS2588 双向联系老师: 点击联系琳琳 【花名】 #琳琳 【地址】 #武侯区 【标签】 #少妇 #自聊 #武侯区 #巨乳 #服务车 #天府三街 (以上是必有标签,其余标签自由发挥) 【车牌】 @LS2588 【硬件】年龄 30 岁左右,身高 160 体重 50KG 罩杯 C 肤色白 无纹身 小蝴蝶 毛量较多 人照 8分 【软件】

Signed 女儿国后宫总管

Showing the 12 most recent of 49 posts we hold for @nverguogk. 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

@nverguogk edited 1 post 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
5 September 2026
Most recent edit
5 September 2026

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 3 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 September 2026 — this entry's latest reading, not the date you are reading this.

“成都•疯狂女儿国后宫🔞” (@nverguogk), 47,854 subscribers as measured 14 September 2026. Telegram Register, tgregister.com/channel/nverguogk.

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.