Education — 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 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 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 sits inside a group of 7 channels linked by matching posts, directly or through other channels in the group; two members of the group may share no posts with each other. 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 (4 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 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 19 comparable posts for this entry, running 9 December 2025 to 2 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.
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 7 channels, the one whose matching posts we hold earliest is @IDS_Math. That channel is not among the channels listed above, so this entry may share no posts with it and this does not say where this entry’s content came from. It 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 7 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. 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.
26 measurements spanning 96 days, net +131. 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 1,389–1,560 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 26
Measured (UTC)
Subscribers
Change
10 Nov 2026, 08:10
1,540
+6
7 Nov 2026, 04:48
1,534
+23
4 Nov 2026, 10:39
1,511
+6
1 Nov 2026, 18:26
1,505
+1
29 Oct 2026, 13:44
1,504
+2
23 Oct 2026, 12:49
1,502
-1
18 Oct 2026, 02:10
1,503
-2
14 Oct 2026, 19:10
1,505
+5
11 Oct 2026, 07:37
1,500
+1
5 Oct 2026, 02:40
1,499
-1
26 Sept 2026, 17:59
1,500
+11
18 Sept 2026, 01:36
1,489
+25
13 Sept 2026, 16:16
1,464
+12
9 Sept 2026, 21:00
1,452
+8
4 Sept 2026, 12:17
1,444
+2
1 Sept 2026, 08:45
1,442
+6
28 Aug 2026, 22:28
1,436
+5
25 Aug 2026, 15:57
1,431
+12
22 Aug 2026, 14:53
1,419
+4
19 Aug 2026, 04:48
1,415
first reading
Engagement
20 posts held, back to 9 December 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 20 posts for this entry, the most recent from 2 August 2026. An engagement rate over an empty window would be a number about nothing.
💖شروع طرح پژوهشی و تربیت پژوهشگر در نوروساینس و علوم شناختی از امروز یکشنبه ساعت 17
❤️ با پشتیبانی 50 استاد و 100 منتور
◀️نحوه ثبت نام در طرح پژوهشی:
https://t.me/IDS_Neuro/1529
‼️همراه با گواهی شرکت در دوره به انگلیسی
🔣کسب اطلاعات بیشتر:
@InterdisciplinarySchools2
🚀|@IDSchools||کانال اصلی|
🚀|@IDS_Neuro||کانال نوروساینس و علوم شناختی|
۱۱ ترفند طلایی برای تسلط بر Claude Code در Google Cloud 🚀
آیا میدانستید روشی که برای تعامل با دستیارهای هوش مصنوعی در پروژههای برنامهنویسی استفاده میکنید، میتواند سرعت توسعه شما را تا ۱۰ برابر افزایش دهد؟ اگر هنوز در حال کپی-پیست کردن کدهای ساده هستید، شما در حال از دست دادن فرصتی بزرگ برای ارتقای سطح کاری خود هستید. در این ویدیوی فوقالعاده کاربردی، ییکی سوگی (YK Sugi) نشان میدهد که چگونه با استفاده از Claud…
💖تنها دو روز به شروع طرح پژوهشی و تربیت پژوهشگر در نوروساینس و علوم شناختی فرصت باقی است!!!
❤️ با پشتیبانی 50 استاد و 100 منتور
◀️نحوه ثبت نام در طرح پژوهشی:
https://t.me/IDS_Neuro/1529
‼️همراه با گواهی شرکت در دوره به انگلیسی
🔣کسب اطلاعات بیشتر:
@InterdisciplinarySchools2
🚀|@IDSchools||کانال اصلی|
🚀|@IDS_Neuro||کانال نوروساینس و علوم شناختی|
🚩🚩🚩🚩🚩🚩🚩🚩🚩
💥 آغاز ثبت نام طرح تربیت پژوهشگر 5 در نوروساینس و علوم شناختی با حضور 50 استاد هیات علمی از دانشگاه های معتبر داخلی و خارجی، با همراهی 100 منتور و ظرفیت 100 تیم پژوهشی- مخصوص همه رشته ها و مقاطع☄️
✨مجموعه علمی و پژوهشی مدارس میان رشته ای با افتخار اعلام می دارد که ثبت نام طرح تربیت پژوهشگر در نوروساینس و علوم شناختی 5 با حضور 50 استاد از اساتید برجسته از خارج و داخل کشور در حوزه های مختلف نوروساینس و علوم…
آموزش و پژوهش در پزشکی - مدارس میانرشتهای pinned «🔴 نحوه ثبت نام در دوره «دیپلم جامع نوروساینس بر اساس کتاب اریک کندل، بخش چهارم» 🔴 ‼️ به اطلاع میرساند که ظرفیت این دوره 30 نفر و شهریه برای ثبت نام در این دوره مجازی 650 هزار تومان است. عزیزان می توانند مبلغ فوق الذکر را به کارت بانکی زیر با شماره 5022…»
‼️ یادآوری- شروع دوره
1️⃣جلسه اول دوره «دیپلم جامع نوروساینس بر اساس کتاب اریک کندل- بخش چهارم»
💖عنوان جلسه اول: تنظیم الگوی سیستم عصبی
⏳زمان برگزاری جلسه اول: پنجشنبه، 4 دی ساعت 17
👤 دکتر لیلا کریمی زندی، دانش آموخته دکتری نوروساینس از دانشگاه علوم پزشکی تهران و عضو هیات علمی دانشگاه
✅ پنجشنبه ها، ساعت 17 تا 19
👈نحوه ثبت نام:
https://t.me/IDS_Med/501
🟢کسب اطلاعات بیشتر:
@interdisciplinaryschools2
🚀|@IDScho…
✨ معرفی دوره های زمستانی در یک نگاه- دومین دوره
⌛عنوان دوره: «دیپلم جامع نوروساینس بر اساس کتاب اریک کندل- بخش چهارم»
🔜 زمان برگزاری جلسه اول: پنجشنبه، 4 دی ساعت 17
🔸سرفصل جلسات:
1️⃣ هفته اول: تنظیم الگوی سیستم عصبی
2️⃣ هفته دوم: تمایز و بقای سلول های عصبی
3️⃣ هفته سوم: مخروط رشد و هدایت آکسون
4️⃣ هفته چهارم: تشکیل و حذف سیناپس ها
5️⃣ هفته پنجم: تجزیه و پالایش یا بهبود اتصالات سیناپسی
6️⃣ هفته ششم: ترمیم مغز آسی…
سلام دوستان🌸😊
نمونه تدریس استاد دوره"دیپلم جامع نوروساینس بر اساس کتاب اریک کندل- بخش چهارم" ، دکتر لیلا کریمی زندی، خدمت شما عزیزان🌸🌹🤓🧠
⭕️اگه سوالی درباره دوره داشتین و یا قصد ثبت نام دارین، کافیه به ادمین کانال به آی دیِ (@interdisciplinaryschools2) پیام بدین🌱🌺
لینک ثبت نام در دوره هم این هست:
💟 https://t.me/IDS_Med/501 💟
🚀|@IDSchools||کانال اصلی|
🚀 |@IDS_Med||کانال آموزش و پژوهش در پزشکی|
🟣 معرفی جلسات 12 گانه دوره «دیپلم جامع کندل بر اساس کتاب اریک کندل- بخش چهارم»- دوره مجازی
💖 شروع دوره: از پنجشنبه این هفته، 4 دی ماه ساعت 17
7️⃣هفته (جلسه) هفتم: تمایز جنسی سیستم عصبی
🗣محتوای این جلسه:
در این فصل، ابتدا پایههای جنینی تمایز جنسی مرور میشوند و سپس به تفاوتهای رفتاری بین دو جنس پرداخته میشود، به ویژه آن تفاوتهایی که پایههای نوروبیولوژیکی مشخصی دارند. این تفاوتها شامل واکنشهای فیزیولوژیک (ما…
🟣 معرفی جلسات 12 گانه دوره «دیپلم جامع کندل بر اساس کتاب اریک کندل- بخش چهارم»- دوره مجازی
💖شروع دوره: از پنجشنبه این هفته، 4 دی ماه ساعت 17
1️⃣هفته (جلسه) اول: تنظیم الگوی سیستم عصبی
🗣محتوای این جلسه:
این فصل به تنوع شگفتانگیز نورونها و سلولهای گلیا در سیستم عصبی مهرهداران میپردازد و نشان میدهد که چگونه انواع مختلف نورونها در موقعیتهای مشخص شکل میگیرند، مورفولوژیهای متفاوت پیدا کرده و با سلولهای هدف …
🟣 معرفی جلسات 12 گانه دوره «دیپلم جامع نوروساینس بر اساس کتاب کندل»- دوره مجازی
2️⃣1️⃣هفته (جلسه یازدهم): تصمیم گیری و آگاهی
🗣محتوای این جلسه:
در این فصل، ما به چگونگی تصمیمگیریهای ادراکی در میمونها میپردازیم، اینکه چگونه این حیوانات در آزمایشگاه، هنگام مواجهه با محرکها و اطلاعات مختلف، انتخاب میکنند. این بررسیها به ما اصول کلی تصمیمگیری را نشان میدهند که نه تنها در حیوانات، بلکه در انسانها و تصمیمات مبت…
Showing the 12 most recent of 20 posts we hold for @IDS_Med. 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
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 10 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
1
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
1
vacant every time we have ever looked
@IDS_Med named 1 handle 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.
@medical_physics_student named in 1 post, 8 August 2026 – 8 August 2026
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
درمان شناختی رفتاری CBT @CBTRAVAN1 · 23,159 Telegram ranks this channel #60 of 88 here — alongside 87 others — read 20 September 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 10 November 2026 — this
entry's latest reading, not the date you are reading this.
“آموزش و پژوهش در پزشکی - مدارس میانرشتهای” (@IDS_Med), 1,540 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/IDS_Med.
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.