Education — 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 23 September 2026 and assigned it the closest of 31 fixed categories, at 100% 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 the other topics.
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 in near-verbatim form on 1 other registered channel. This entry also forms a group of 2 channels linked by matching posts. 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 (3 of the pairs behind the counts below)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
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 0 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 16 comparable posts for this entry, running 22 November 2025 to 20 June 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).
Of the group of 2 channels, the one whose matching posts we hold earliest is @SCMED_Larestan — 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 11 November 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.
Channels linked by matching posts
This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim 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.
12 measurements spanning 90 days, net -5. 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 257–265 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
5 Nov 2026, 22:06
259
-1
29 Oct 2026, 08:20
260
-2
16 Oct 2026, 03:06
262
+1
9 Oct 2026, 16:00
261
+1
28 Sept 2026, 12:55
260
+2
15 Sept 2026, 07:58
258
-1
7 Sept 2026, 08:01
259
-2
28 Aug 2026, 21:44
261
-1
21 Aug 2026, 06:53
262
-1
15 Aug 2026, 03:28
263
-1
8 Aug 2026, 09:03
264
no change
7 Aug 2026, 15:13
264
first reading
Engagement
17 posts held, back to 22 November 2025 — 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 page of 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 17 posts for this entry, the most recent from 20 June 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
5 reactions across 4 posts, in 3 distinct kinds. The most used accounts for 60.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
3
60.0%
👏
1
20.0%
💯
1
20.0%
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 6 of the 17 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 5 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 17 most recent posts we hold, published 22 November 2025 to 20 June 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.
💡 به کانال آموزشی پرهانترنی و دستیاری هایلایت خوش اومدین.
⚜ اینجا تجربیات خودم و بسیاری از رتبههای برتر سالهای گذشته رو در مورد آزمونهای پرهانترنی و دستیاری پزشکی، در قالب چنتا پست براتون گذاشتم.
⚜ وجه تمایز این کانال با کانالهای مشابه، در نحوهٔ مطالعهایه که برای کتب QB ارائه کردم. برای دوستانی که حوصله یا وقت کافی برای آمادهکردن کتب QB به روشی که گفتم رو ندارن، مجموعهای تحت عنوان راهنمای هایلایت به تدریج …
🎓دوره دیپلم جامع پژوهشی
🔍یادگیری گامبهگام پژوهش تا نگارش و چاپ مقاله
💠با تدریس اساتید برجسته ملی و بین المللی از جمله:
👤دکتر کامران باقری لنکرانی
🔹وزیر اسبق بهداشت، درمان و آموزش پزشکی
🔹عضو بینالمللی انجمن گوارش آمریکا
🔹نویسنده ۶۰۶ مقاله بین المللی
🔹دارای h-index= ۵۲
🔹استاد تمام دانشگاه علوم پزشکی شیراز
🔹دانشمند ۱ درصد برتر دنیا
👤دکتر رضا ملک زاده
🔹وزیر اسبق بهداشت، درمان و آموزش پزشکی
🔹نگارنده ۱۰۳۰ مقاله بینا…
🎓✨ آموزش علوم پزشکی در حال تحول ✨🎓
کارگروه تغذیه و علوم غذایی
کمیته دانشجویی توسعه آموزش علوم پزشکی شیراز با همکاری کمیته دانشجویی توسعه آموزش علوم پزشکی دانشگاه علوم پزشکی لرستان برگزار میکند:
🔍 بررسی فرصتها و چالشهای آموزش پزشکی در عصر حاضر
👤 مدرس: آقای محمد سوری
🔹 منتور جشنوارههای ایدههای نوآورانه آموزشی
🔹 برگزیده کشوری المپیاد دانشجویان وزارت بهداشت (کارآفرینی)
🔹 مدرس و پژوهشگر حوزه هوش مصنوعی
🔹 دبیرکل کم…
✨ آوینا؛ آفرینش و ایدههای نوآورانه آموزشی ✨
📌 اولین دوره جشنواره دانشجویی آوینا
به میزبانی کمیته دانشجویی توسعه آموزش علوم پزشکی دانشگاه علوم پزشکی شهید بهشتی
و با همکاری کمیتههای دانشجویی توسعه آموزش شیراز و لرستان برگزار خواهد شد.
🎓 جشنواره آوینا با رویکردی خروجیمحور و با هدف توانمندسازی دانشجویان علوم پزشکی برگزار میشود و شامل:
🔹 سلسله کارگاههای آموزش پزشکی و ایدهپردازی
🔹 گروهبندی دانشجویان
🔹 منتورینگ اید…
❤️🩺جامعترین دوره قلب؛ آموزش کیسمحور از تفسیر نوار قلب تا تصمیمگیری بالینی و جراحیهای قلبی
📚سرفصلهای دوره:
▪️بیماریهای شایع قلب (دکتر منوچهر قانونی)
▪️ تفسیر کامل نوار قلب (ECG)
▪️ تفسیر آزمایشهای قلب
▪️ تفسیر کامل عکسبرداری قفسه سینه
▪️ شرح حال و معاینه قلب
▪️ آشنایی با جراحیهای قلب
🗓 20 جلسه آموزشی تخصصی
⏱بیش از 30 ساعت آموزش جامع و کاربردی
🪙با تخفیفی کمنظیر
1980 هزار تومان❌
↘با تخفیف ویژه فقط 299 هزار ت…
📢کمیته دانشجویی توسعه آموزش علوم پزشکی با همکاری انجمن علمی رشته پرستاری دانشکده پرستاری و فوریت های پزشکی البرز برگزار می کند:
🧠سلسله کارگاه های مراقبت ویژه مغز و اعصاب
📝براساس آخرین گایدلاین ها
📚جلسه اول:
📕امتیازدهـی (scoring)
🔹دبیر علمی:
🔸خانم دکتر سیما سادات حجازی
🔹عضو هیئت علمی دانشکده پرستاری و فوریت های پزشکی البرز
🗣مدرسان:
👩🏻⚕️خانم شقایق افضلنیا
🎖دانشجوی کارشناسی ارشد پرستاری مراقبت های ویژه دانشگاه عل…
📣 کمیته دانشجویی توسعه آموزش دانشکده پرستاری دانشگاه علوم پزشکی بقیه الله (عج) با همکاری مدیریت امور دانشجویی سازمان نظام پرستاری کشور برگزار میکند ...
✅ عنوان : وبینار آموزشی تهویه مکانیکی پایه
🔻 سرفصل ها
مفاهیم تهویه مکانیکی
اندیکاسیونهای تهویه مکانیکی
تنظیمات تهویه مکانیکی
بررسی مدهای پایه
مدیریت انواع آلارم ونتیلاتور
💻 مدرس: جناب آقای باقر آغال
دانشجوی دکتری تخصصی پرستاری
مدرس کشوری دورههای مراقبت ویژه
🎯…
📢کمیته دانشجویی توسعه آموزش علوم پزشکی با همکاری انجمن علمی رشته پرستاری دانشکده پرستاری و فوریت های پزشکی البرز برگزار می کند:
🧠سلسله کارگاه های مراقبت ویژه مغز و اعصاب
📝براساس آخرین گایدلاین ها
📚سرفصل های آموزشی کارگاه:
📕امتیازدهـی (scoring)
📗تروما به سر و آسیب مغزی
📘فشار داخل جمجمهای (ICP)
📙سکته مغـزی (CVA)
📕خونریزی تحت عنکبوتیه (SAH)
📗پیشگیـری از سکته مغزی
🎓ویژه تمامی دانشجویان علوم پزشکی
✅همراه با گواهی معتب…
📣 کمیته دانشجویی توسعه آموزش دانشکده پرستاری دانشگاه علوم پزشکی بقیه الله (عج) با همکاری مدیریت امور دانشجویی سازمان نظام پرستاری کشور برگزار میکند ...
✅ عنوان : وبینار آموزشی تهویه مکانیکی پایه
🔻 سرفصل ها
مفاهیم تهویه مکانیکی
اندیکاسیونهای تهویه مکانیکی
تنظیمات تهویه مکانیکی
بررسی مدهای پایه
مدیریت انواع آلارم ونتیلاتور
💻 مدرس: جناب آقای باقر آغال
دانشجوی دکتری تخصصی پرستاری
مدرس کشوری دورههای مراقبت ویژه
🎯…
🌀 کمیته مرکزی دانشجویی توسعه آموزش علوم پزشکی وزارت بهداشت، درمان و آموزش پزشکی به میزبانی کمیته دانشجویی توسعه آموزش علوم پزشکی یزد و با همکاری کمیته های دانشجویی توسعه آموزش علوم پزشکی سمنان، سبزوار، زاهدان و تهران برگزار میکند:
💡مجموعه کارگاههای مجازی مبانی آموزش پزشکی
3️⃣جبرانی جلسه سوم
🔹با عنوان
🌟یادگیری خود راهبر🌟
📆سه شنبه ۱۸ آذر ماه ۱۴۰۴
⏰ ساعت ۱۸ الی ۲۰
✨با تدریس
🎖سرکار خانم دکتر رقیه گندمکار
• دکترای تخ…
Showing the 12 most recent of 17 posts we hold for @SCMED_Larestan. 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.
Forward network
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.
Mentions
Named by 2 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.
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.
Handles this channel named that no longer answer
Dead references
3
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
3
vacant every time we have ever looked
@SCMED_Larestan named 3 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@faramed_admin named in 1 post, 9 August 2026 – 9 August 2026
@mohammad_tousii named in 1 post, 9 August 2026 – 9 August 2026
@systematic_course named in 1 post, 9 August 2026 – 9 August 2026
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 5 November 2026 — this
entry's latest reading, not the date you are reading this.
“کمیته دانشجویی توسعه آموزش علوم پزشکی،لارستان” (@SCMED_Larestan), 259 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/SCMED_Larestan.
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.