Channel
@icebteakitchen
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
4,098subscribers
+9 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1002574980549 |
|---|---|
| Type | Channel |
| Username | @icebteakitchen |
| Created | Between 1 March 2025 and 31 July 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 10 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 10 August 2026 |
| On Telegram | t.me/icebteakitchen |
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 87% 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.
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.
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.
| Posted first | Then | Overlap | Gap |
|---|---|---|---|
| @Tomcatnotes/3928 Apr 2026, 07:38 UTC | @icebteakitchen/43 · this entry28 Apr 2026, 07:38 UTC | 1.00 | under a minute |
| @Tomcatnotes/445 May 2026, 07:28 UTC | @icebteakitchen/46 · this entry5 May 2026, 07:28 UTC | 1.00 | under a minute |
| @icebteakitchen/53 · this entry28 May 2026, 09:35 UTC | @Tomcatnotes/5128 May 2026, 09:35 UTC | 1.00 | under a minute |
| @Tomcatnotes/5718 Jun 2026, 11:17 UTC | @icebteakitchen/55 · this entry18 Jun 2026, 14:56 UTC | 1.00 | 3.7 hours |
| @Tomcatnotes/5920 Jun 2026, 06:00 UTC | @icebteakitchen/56 · this entry20 Jun 2026, 06:00 UTC | 1.00 | under a minute |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @Tomcatnotes | 5 (5/5 hand-verifiable sample passed) | 1.00 | under a minute | this entry (3–2) |
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. None of the 1 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 17 comparable posts for this entry, running 22 April 2026 to 5 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.
Across the whole group of 2, the earliest publisher we hold is @icebteakitchen — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_mutual, 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.
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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Aug 2026, 07:25 | 4,098 | +7 |
| 7 Aug 2026, 11:24 | 4,091 | +2 |
| 6 Aug 2026, 20:31 | 4,089 | first reading |
18 posts held, back to 22 April 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 4 pagesof Telegram’s post history, 20 posts per page.
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 3 of 4 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 5 August 2026 |
|---|---|
| Posts held | 18 (22 April 2026 – 5 August 2026) |
| Views total | 8,783 |
| Reactions total | 5 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Aug 2026, 05:37 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.
Measured directly from 5 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.
42 reactions across 12 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 42 | 100.0% |
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 13 of the 18 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 42reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 22 April 2026 to 5 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.
照片不是本人，本人颜值很高，看评分 老师名字：吱吱 老师电报号： @ZhizhiyaOvO 硬件： 颜值 4.50（五官动过，脸小，底子不错） 妆品 4.50（不卡粉，妆品不错，颜值属于回头率很高的那种） 身高体重 168cm 40kg（身材） 皮肤 4.25（白皮，皮肤很好，细腻，光滑，髋部有点淡淡的胎记） 胸 3.75（D+ 人工胸，乳头乳晕又小又粉，这胸大价钱了，目前摸到最软的do胸了） 腰 4.50（妹子80斤，细致结硕果类型，腰细基本没赘肉） 臀 4.00（小批过翘臀，髋部不大） 腿 4.00（细白大支腿，很细，很直，比例也不错） 足 4.00（正常足） 逼 4.50（毛毛天然很少，就一丢丢，下面粉色） 软件： 陪浴 4.25（可以浴室调情，水中萧，胸推，提一下都会） 亲嘴 4.50（舌吻管够，大蟒蛇都可以，颜值高亲吻很有感觉） 口活 4.25（妹子嘴巴很小，包裹感很舒服，有一丢丢齿感） 舔逼 4.00（没舔，…
❤1
老师名字：洋洋 老师电报号： @linxx199123 硬件： 颜值 3.75（刚做了鼻子，20多天，五官还可以，科技痕迹有） 妆品 4.25（不卡粉，很贴肤，唇彩也不错） 身高体重 165cm 46kg（身材） 皮肤 4.50（白皮，皮肤细腻光滑，没有一点纹身，皮肤白的发光，唯一缺点就是肋骨鼻疤痕刚刚好，而且没有增生，平平的一道） 胸 4.75（c+天然腺体胸，乳头乳晕又小又粉，而且挺拔，初看见我还以为是做的，一摸纯天然） 腰 4.50（腰细，而且前部腹肌有线条，腹肌是凸起的，边上两条清晰线条） 臀 4.75（髋很宽，屁股的肉又挺又翘，我也以为是脂肪填充的，但是妹子是天然且无冲脂痕迹） 腿 4.00（腿部相对比例正常，很白很直的腿） 足 4.00（很白，正常足） 逼 4.00（前部毛毛正常，阴部肉粉色，阴唇两边毛毛很少很细，提醒她可以挂掉） 软件： 陪浴 4.00（主动帮洗，全程仔细，妹子胸部极品，屁股也翘，已经教了素…
老师名字：米米 （可以和汐汐双飞 @ReneHart2012 ） 老师电报号： @x87679437 硬件： 颜值 4.25（颜值比照片要更好看一点，鼻子动过，整体五官偏精致） 妆品 4.25（妆品服帖） 身高体重 163cm 47kg（身材） 皮肤 3.75（正常黄皮，锁骨有点小纹身，有肋骨鼻疤，肚脐上方有个内窥镜小疤） 胸 4.25（c左右的天然胸，乳头乳晕大小颜色正常） 腰 4.00（腰身不错，很细） 臀 4.00（正常臀，肉感不错，挺翘度一般） 腿 4.00（腿比例不错，正常比例，大腿没有赘肉） 足 3.75（指甲油没有，足部正常） 逼 4.00（无毛白虎，略微色素沉淀） 软件： 陪浴 4.5（胸推，素股，水中萧都有，事前事后陪浴很认真） 亲嘴 4.75（大蟒蛇，进攻性很强） 口活 4.25（很舒服，速度有点快！） 舔逼 4.00（敏感，反馈很好） 其他服务（见课表） 屌感 4.25（很浅，且包裹性很不错，…
❤3
老师名字：汐汐 老师电报号： @ReneHart2012 硬件： 颜值 4.5（人照9分，脸小，没有任何整容痕迹，充满了青春荷尔蒙，五官都很小巧，嘟嘟小嘴。) 妆品 4.5（不卡粉，青春淡妆） 身高体重 165cm 40kg（身材） 皮肤 4.0（正常黄皮，右小腿有纹身，不low，皮肤细腻爽滑) 胸 4.00（b+天然少女胸，乳头乳晕很小，颜色正常) 腰 4.00（腰身很细，骨架很小，有一丢丢小肚子，不伤大雅) 臀 4.25（非常小巧的小翘屁股，有两道腰痕，后背曲线很不错。) 腿 4.00（腿比例很不错，正常粗细，没有赘肉) 足 4.5（指甲油很好看，小嫩足） 逼 4.75（馒头b，微微隆起，无毛，且嫩，内粉色，看到就忍不住的那种) 软件： 陪浴 4.5（全程主动帮忙洗漱，事后洗，胸推，素股都会做，特别是素股，小屁股很认真的会扭动，作为一个嫩妹有这样的服务，实属难得) 亲嘴 4.75（青涩的舌吻，小嘟嘟嘴可蟒蛇，妹子都不…
❤1
老师名字： 羞羞 老师电报号： @XIU123098 硬件： 颜值 3.75（人照一致，妆品不错） 妆品 4.00（化妆很服帖，不卡粉） 身高体重 160cm 50kg（有点微胖了） 皮肤 3.75（黄皮，有纹身） 胸 3.75（少女胸，B-C之间，天然，挺） 腰 3.25（有点婴儿肥，腰身不算细） 臀 4.00（屁股很翘，弹性好） 腿 3.25（腿正常，有点肉且肉很紧实） 足 3.75（小肉脚） 逼 4.50（人工白虎，双阴道，超级紧） 软件： 陪浴 4.0（服务都有，水中萧，胸推，素股也会了） 亲嘴 4.25（舌吻管够，很听话） 口活 4.00（无齿感，舌头灵活，包裹感不错） 舔逼 4.00（没有异味，很敏感） 其它服务 （见课表） 屌感 4.75（真的紧，而且包裹感很舒服） 爱爱 4.5（全程投入，感觉到不错的反馈） 情绪价值 4.25（能说会道，很能夸人，聊天不做作） 特殊技能…
❤2
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抽奖编号：L178175724316 抽奖标题：端午节 白嫖抽奖 抽奖说明：米其林豌豆 举办频道关注活动 https://t.me/godagent007/411 关注豌豆的频道和各位特工的频道，参加端午抽奖 参与条件： 🎫 必须有用户名 🎫 加入-魔都光明顶教学课程展览室2 🎫 加入-特工验证榜 🎫 加入-魔都光明顶总舵入口 🎫 加入-豌豆朋友圈 🎫 加入-圣火喵喵教 🎫 加入-夢遊日記2.0 🎫 加入-ZHAO 片集 🎫 加入-Tom猫的笔记 🎫 加入-9拆盲盒 🎫 加入-心有灵犀一点通 🎫 加入-《七宗罪》实录 🎫 加入-灭火救援台账 🎫 加入-床头柜先生的日常 🎫 加入-水月洞天_二月红 🎫 加入-🍵伯昌君的休假记录 🎫 加入-风林渡口初相遇 奖品内容： 💰️ 55的红包 × 2 💰️ 米其林豌豆单p免单 × 1 开奖条件：2026-06-24 14:00自动开奖 参与抽奖链接：https://t.me/cutelott…
❤1
老师名字： 小羊 老师电报号： @little1sheep 硬件： 颜值 4.25（嫩妹，眉心有个很淡月形小凹疤，底子很不错，颜值嫩妹） 妆品 4.25（妆品非常好，服帖，细腻白皙） 身高体重 164cm 46kg 皮肤 4.25（皮肤不错，很细腻，肤色白） 胸 4.00（天然B+，一只手刚好，乳头乳晕小） 腰 4.00（腰细，腰腹平坦，略有点小肚子） 臀 4.25（很小的紧致屁股，后入小屁股） 腿 4.25（很直，很细，且白皙） 足 4.00（正常足，整洁，干净的小脚） 逼 3.75（毛偏卷，不多，内粉色） 软件： 陪浴 4.25（浴室有水中箫，素股臀推） 亲嘴 4.00（舌吻管够，小舌头灵活） 口活 4.00（很耐心，且乖，无明显齿感） 舔逼 4.00（淡淡香气，有反馈，敏感） 其它服务 （见课表） 屌感 4.25（感觉没怎么做过，屌感很紧，且浅） 爱爱 4.00（很努力，什么姿势都配…
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❤3
全部评分项目17 个，满分5分制度，最终去掉一个最高分和最低分，按照平均分予以评级，只针对妹子素质客观评级： 老师名字： 李不苒 老师电报号： @SHliburan1 硬件： 颜值 4.5 （纯真少女，没风尘味，皮肤超级白，小雀斑超级可爱，加分) 妆品 4.5 （妆品很不错，脸上不卡粉，天生太白了) 身高体重 160cm 45kg（白幼萝莉身材） 皮肤 4.0 （皮肤太白了，白的厉害，缺点是洗澡洗多了，有点干，平时护肤露一定要保养涂) 胸 4.0 （纯天然B杯少女胸，乳头乳晕很小，少女胸！) 腰 3.5 （很细，不过前面有点婴儿肥小赘肉了，不严重) 臀 4.00 （屁股肉多了，很duangduang，抱着贼有肉感) 腿 3.75 （腿不长，上面偏粗，整体很嫩) 足 4.00 （超级嫩脚，小足，没图指甲油都好嫩！) 逼 4.50 （修剪了毛毛，前面留着，两边剃光了，好粉) 软件： 陪浴 4.00 （教…
❤11
菜品描述： 妹子属于批发市场销售（详情请参考 https://t.me/icekitchen/853 ） 名字：安婷 电报号： @antingshmh05 身高：170 体重：49KG 罩杯：C 价格：1000p 时长：50分钟 1500pp 时长：90分钟 妹子评价：（满分5分） 颜值：3分 重庆妹子，颜值和视频9成像，略微比视频脸大一丢丢，妹子皮肤正常黄皮，皮肤非常细腻，无纹身，长相和好歌手陈冰很像。颜值算中上。 情绪价值：4分 基本满分，很直爽，直…
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老师名字： Ginababycc 老师电报号： @Ginababycc 硬件： 颜值 4.5（人照基本一致，五官小巧，脸很小，颜值不错，路上回头率不低的精灵系女孩） 妆品 4.5（化妆水平不错，不卡粉，妆容精致） 身高体重 164cm 46kg（） 皮肤 4.75（冷白皮，很滑，小纹身有，后背脊梁骨一条细细的纹身，很高级，皮肤真的没得说，又白又滑） 胸 4.75（真胸，c+，胸型也很不错，乳晕乳头粉嫩，乳头适中，算是上品了） 腰 5（细腰，没有一点赘肉，算是那种夜店的水蛇腰） 臀 4.5（翘屁股，又白又翘） 腿 4.0（腿不算长，但是很直，小腿很细） 足 5.0（目前见过最漂亮的脚，很白，小，指甲油和好看，关键嫩的一塌糊涂） 逼 4.75（粉嫩白虎逼，人工的，很粉很嫩，有微微香气） 软件： 陪浴 0（妹子每天涂身体乳，皮肤保养的很好，说洗多了伤皮肤，所以没有陪浴） 亲嘴 4.75（大蟒蛇，舌吻很主动，…
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Showing the 12 most recent of 18 posts we hold for @icebteakitchen. 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 — 251,366 of 1,151,006entries 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.
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.
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.
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.
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.
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 10 August 2026 — this entry's latest reading, not the date you are reading this.
“冰哥的米其林厨房” (@icebteakitchen), 4,098 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/icebteakitchen.
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.