Channel
@shengxiaoguan
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
59subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001234341421 |
|---|---|
| Type | Channel |
| Username | @shengxiaoguan |
| Description | @ovler 的个人channel 为什么肾小管-排垃圾，重吸收。 随意转发 |
| Created | Between 1 March 2018 and 31 July 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 10 August 2026 |
| Last confirmed live | 16 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/shengxiaoguan |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Aug 2026, 06:00 | 59 | no change |
| 7 Aug 2026, 19:01 | 59 | first reading |
18 posts held, back to 13 February 2023 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 18 posts for this entry, the most recent from 3 August 2025. An engagement rate over an empty window would be a number about nothing.
Lifetime counters from Telegram’s own channel header, read 10 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Measured directly from 2 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.
11 reactions across 7 posts, in 5 distinct kinds. The most used accounts for 36.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 4 | 36.4% | |
| 🤔 | 3 | 27.3% | |
| 🤯 | 2 | 18.2% | |
| 🎉 | 1 | 9.09% | |
| 👍 | 1 | 9.09% |
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 7 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 11reactions 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 13 February 2023 to 3 August 2025, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
（转自qq空间，已查证 土豆它妈是番茄…… 手里的薯条番茄酱突然变成亲子丼了……… 中国科学家证实番茄是土豆的杂交母本，成果于7月31日发表于细胞Cell 原文：Ancient hybridization underlies tuberization and radiation of the potato lineage, https://www.cell.com/action/showPdf?pii=S0092-8674%2825%2900736-6 https://doi.org/10.1016/j.cell.2025.06.034
🤯2
https://lllyasviel.github.io/pages/paints_undo/ AI也会一步步画画喽 虽然类似于一步步撤销
🤔1
https://arxiv.org/abs/2402.17764 1.58bit (ternary parameters 1,0,-1) LLMs, showing performance and perplexity equivalent to full fp16 models of same parameter size. Implications are staggering. Current methods of quantization obsolete. 120B models fitting into 24GB VRAM. Democratization of powerful models to all with consumer GPUs. https://www.reddit.com/r/LocalLLaMA/comments/1b21bbx/this_is_pretty_revolutionary_for_…
❤2👍1
https://t.me/loveuchangeless/4210 https://t.me/loveuchangeless/4211 https://t.me/loveuchangeless/4233 非常好的关于读博的建议和分享。
❤2
https://omnimotion.github.io/ Tracking Everything Everywhere All at Once 实时跟随！！！
Video, posted without a caption
https://github.com/XingangPan/DragGAN https://vcai.mpi-inf.mpg.de/projects/DragGAN/ GAN杀回来了！！！
【罗肖尼】如何永远学会一个单词？ @罗肖尼Shawney: 〰〰〰〰〰〰〰〰〰〰 🔝> @罗肖尼Shawney: 视频内容梗概—— 第一章：三个难题 * 任意符号难题——记住单词如同记住一个任意的名字，而纯背单词所得到的记忆脆弱易失 * 宽度难题——单词知识如海洋一般宽阔，纯背单词就像用木桶舀海般捉襟见肘 * 深度难题——单词知识如井水一般深邃，纯背单词只能触及单词知识的表层 第二章：语境的力量 * 词汇如丝线、文本如织品，我们在语境中才能感受词汇的生命 * 要用图像、声音、事件、情感将词汇符号固定在记忆中 * 如果每读/听一百个词只遇到2个或更少生词（可理解输入），我们便可以像拼拼图一样从语境中推测、学会生词的意义 * 大部分的单词都需要我们在变化的语境中重复至少12次，才能被我们充分学会 幕间：语言传奇 * 掌握15门外语的匈牙利翻译家Lomb Kato的秘密武器是读原著闲书 * “只有阅读才能带来（单词的）无限重复” 第三…
🤔1
🍰
📰 Marked in #Curius at 2023-03-26. Write by 和菜头 从邀请码到等待名单
（转
📰 Marked in #Curius at 2023-03-12 两会后的一些分享
Showing the 12 most recent of 18 posts we hold for @shengxiaoguan. 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.
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.
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.
“肾小管” (@shengxiaoguan), 59 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/shengxiaoguan.
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.