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Channel

不是白嫖,这叫借鉴(备用)

@baipiaou

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

34,446subscribers

+3,334 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-1002576291526
TypeChannel
Username@baipiaou
Description简单粗暴,严选分享,每一条都实用! 投稿、广告联系:@czp666
CreatedBetween 1 March 2025 and 31 July 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live25 September 2026
Measurements held36
Confirmed unchanged1 time, most recently 25 September 2026
On Telegramt.me/baipiaou

Topic

Technology — 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 99% 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

31,11234,44632,7796 August 2026 — 31,112 subscribers6 August 2026 — 31,135 subscribers7 August 2026 — 31,160 subscribers8 August 2026 — 31,226 subscribers9 August 2026 — 31,296 subscribers10 August 2026 — 31,330 subscribers11 August 2026 — 31,377 subscribers12 August 2026 — 31,436 subscribers13 August 2026 — 31,490 subscribers14 August 2026 — 31,545 subscribers16 August 2026 — 31,674 subscribers17 August 2026 — 31,778 subscribers18 August 2026 — 31,836 subscribers19 August 2026 — 31,876 subscribers20 August 2026 — 31,967 subscribers21 August 2026 — 32,046 subscribers23 August 2026 — 32,228 subscribers25 August 2026 — 32,369 subscribers25 August 2026 — 32,422 subscribers26 August 2026 — 32,479 subscribers27 August 2026 — 32,536 subscribers28 August 2026 — 32,561 subscribers29 August 2026 — 32,617 subscribers30 August 2026 — 32,676 subscribers31 August 2026 — 32,737 subscribers1 September 2026 — 32,779 subscribers2 September 2026 — 32,819 subscribers3 September 2026 — 32,855 subscribers5 September 2026 — 32,962 subscribers8 September 2026 — 33,265 subscribers11 September 2026 — 33,433 subscribers13 September 2026 — 33,572 subscribers14 September 2026 — 33,700 subscribers16 September 2026 — 33,832 subscribers19 September 2026 — 34,020 subscribers25 September 2026 — 34,446 subscribers6 August 202625 September 2026
36 measurements spanning 51 days, net +3,334. 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 30,612–34,946 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 36
Measured (UTC)SubscribersChange
25 Sept 2026, 17:5834,446+426
19 Sept 2026, 02:5834,020+188
16 Sept 2026, 15:5833,832+132
14 Sept 2026, 21:5833,700+128
13 Sept 2026, 05:3633,572+139
11 Sept 2026, 10:3733,433+168
8 Sept 2026, 19:1633,265+303
5 Sept 2026, 15:5632,962+107
3 Sept 2026, 14:1932,855+36
2 Sept 2026, 09:0632,819+40
1 Sept 2026, 08:4632,779+42
31 Aug 2026, 07:4432,737+61
30 Aug 2026, 10:2432,676+59
29 Aug 2026, 12:2432,617+56
28 Aug 2026, 15:4132,561+25
27 Aug 2026, 19:1332,536+57
26 Aug 2026, 22:1432,479+57
25 Aug 2026, 23:5932,422+53
25 Aug 2026, 00:4432,369+141
23 Aug 2026, 10:4632,228first reading

Engagement

85 posts held, back to 23 July 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 92 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
20.6%
avg views ÷ 34,446 subscribers
Avg views / post
7,080
38 posts measured
Reaction rate
0.056%
reactions ÷ views · ER floor
Posts in window
38
of 85 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 29 September 2026
Posts held85 (23 July 2026 – 29 September 2026)
Views total269,062
Reactions total151
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken29 Sept 2026, 06:52 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
≈1,130
Links
≈1,140

Lifetime counters from Telegram’s own channel header, read 29 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.

Reaction mix

341 reactions across 79 posts, in 8 distinct kinds. The most used accounts for 75.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤25875.7%
👍6819.9%
💩61.76%
👎30.88%
😁20.587%
🤮20.587%
👏10.293%
🕊10.293%

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 84 of the 85 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 344 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 85 most recent posts we hold, published 23 July 2026 to 29 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

29 Sept 2026, 02:30 UTC832 views1 reactionsread 29 September 2026
Photo

公务员考试行测真题 覆盖了2016-2026,515套卷,5万多道题,按行测模块分门别类,题干、选项、答案、官方解析齐全,也可蒸馏让AI研究题型、思路等,里面有蒸馏教学手册~ https://github.com/ERRRC/xingcezhenti 📖频道 | 📥投稿 | 🌐商务 #Github #考公 #备考

👍1

28 Sept 2026, 02:15 UTC≈2,730 views1 reactionsread 29 September 2026
Photo

一个接进 Codex 的旅行规划工具 先出几条路线让你挑,确认后再去查交通、住宿、天气、当地玩法,最后打包成能直接打开的 HTML 页面~ https://github.com/mater1996/travel-planning 📖频道 | 📥投稿 | 🌐商务 #Github #旅游 #Agent

👍1

27 Sept 2026, 04:00 UTC≈4,320 views0 reactionsread 29 September 2026

#频道互推 #群组推荐 尤物色色导航 无双资源分享-破解/VPN/美图 万卷书屋/小说推荐/禁忌书屋 纸鸢分享社-破解软件|游戏分享 iOS破解游戏软件分享 电影资源频道(4K、原盘) 爱游戏分享社 破解软件/VPN/资源/精选分享 安卓黃油の领域(转世重生) 弈泽 - 审计级财报分析系统

27 Sept 2026, 02:35 UTC≈4,320 views3 reactionsread 29 September 2026
Photo

开源的 AI 盯盘助手 能帮你盯着 A 股、港股、美股,盘前给策略、盘中盯异动、盘后写复盘,新闻来了自动筛选跟持仓相关的~ https://github.com/TNT-Likely/PanWatch 📖频道 | 📥投稿 | 🌐商务 #Github #AI #投资理财

❤2👍1

25 Sept 2026, 11:00 UTC≈5,530 views4 reactionsread 29 September 2026

#互推 【转存&引流】媒体托管机器人 【书籍小说】万卷书屋/小说推荐/禁忌书屋 【音声&涩涩】永不消逝的音声 【影视分享】观影视界[GyWEB] 【炒币资讯】币圈快讯 【机场测评】小众机场测评 【网络分享】不是白嫖,这叫借鉴(备用) 【软件分享】TK集库 【节点分享】FFQ Cloud 订阅|id分享中心 Powered by @Summer_Clear_Sky_Bot

❤4

25 Sept 2026, 02:23 UTC≈7,820 views4 reactionsread 29 September 2026
Photo

能把任何书籍转化成Skill 比如民法典、劳动法,原文十几万字,做成Skill后AI直接基于法条原文回答,而不是编造不确定的答案~ https://github.com/virgiliojr94/book-to-skill 📖频道 | 📥投稿 | 🌐商务 #Github #Agent #Skill

❤4

24 Sept 2026, 02:05 UTC≈6,320 views2 reactionsread 29 September 2026
Photo

AI参谋,聊天辅助工具 告诉你对方想干什么,有没有坑,给几条回复建议,安卓端支持微信、QQ、飞书等,mac端仅支持微信,最终回复权仍在自己手里~ 安卓端:https://github.com/jev-chat/jev-chat-jarvis mac端:https://github.com/jev-chat/jev-chat-jarvis-mac 📖频道 | 📥投稿 | 🌐商务 #Github #AI #安卓 #mac

❤2

23 Sept 2026, 02:20 UTC≈7,050 views1 reactionsread 29 September 2026
Photo

AI短剧大佬的新作 描述任何想要的场景,AI会生成白模和提示词,直接丢给seedance就能完美还原,也可以实现自动化流程:AI 读剧本 → 自动生成三维预演 → 导出参考视频和提示词 → 再交给seedance,实现短剧从文本到画面的半自动化生产~ https://github.com/mangfufu/director-desk 📖频道 | 📥投稿 | 🌐商务 #Github #短剧 #AI

❤1

22 Sept 2026, 02:05 UTC≈6,800 views6 reactionsread 29 September 2026
Photo

一边打字一边学语言 无论是学习日语还是英语,当你输入文字时,候选词旁边会跟一行你正在学的语言的翻译,不打断、不知道强迫记忆,轻松提高英语、如日语等~ https://github.com/qingjian-team/qingjian 📖频道 | 📥投稿 | 🌐商务 #Github #学习 #英语 #日语

👍4❤2

21 Sept 2026, 02:07 UTC≈8,980 views4 reactionsread 29 September 2026
Photo

好用的GKD去广告规则 GKD是安卓的开源软件,主要用于去开屏广告的,这个好用,天天更新,三个全局规则基本够用,就能控制全部开屏广告~ 👉🏻GKD下载 👉🏻好用的去广告规则 📖频道 | 📥投稿 | 🌐商务 #Github #安卓 #去广告

👍4

20 Sept 2026, 04:00 UTC≈7,540 views1 reactionsread 29 September 2026

#频道互推 #群组推荐 万卷书屋/小说推荐/禁忌书屋 无双资源分享-破解/VPN/美图 JBCAT优质壁纸走私 黄油批发(优质黄油分享) 安卓黃油の领域(转世重生) 吃瓜小队 Magazine杂志 飞鱼资源分享|工具软件 小声逼逼· 软件|Emby|抽奖 弈泽 - 审计级财报分析系统

❤1

20 Sept 2026, 02:05 UTC≈7,390 views3 reactionsread 29 September 2026
Photo

261 种手绘插画风格 看图选风格很方便,选择你想要的风格,告诉AI你想要什么画,用codex生成效果很好~ https://github.com/yang0/handraw-style 📖频道 | 📥投稿 | 🌐商务 #Github #Agent #Skill

❤2👍1

Showing the 12 most recent of 85 posts we hold for @baipiaou. 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

@baipiaou 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
15 August 2026
Most recent edit
22 August 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 16 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 25 September 2026 — this entry's latest reading, not the date you are reading this.

“不是白嫖,这叫借鉴(备用)” (@baipiaou), 34,446 subscribers as measured 25 September 2026. Telegram Register, tgregister.com/channel/baipiaou.

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.