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 10 August 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 why it has no browse page of its own yet.
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 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.
Matching posts — open both and compare (2 of the pairs behind the counts below)
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 18 comparable posts for this entry, running 22 July 2026 to 6 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).
Across the whole group of 2, the earliest publisher we hold is @IPhSAIran — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, 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.
Also posting the same content
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.
11 measurements spanning 29 days, net +215. 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 9,133–9,412 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
4 Sept 2026, 13:36
9,380
+66
1 Sept 2026, 04:18
9,314
+37
29 Aug 2026, 06:53
9,277
+17
26 Aug 2026, 09:41
9,260
+5
23 Aug 2026, 07:38
9,255
+2
19 Aug 2026, 13:27
9,253
+35
16 Aug 2026, 08:58
9,218
+2
13 Aug 2026, 06:17
9,216
+7
10 Aug 2026, 14:15
9,209
+34
7 Aug 2026, 06:24
9,175
+10
6 Aug 2026, 06:33
9,165
first reading
Engagement
78 posts held, back to 22 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 32 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
16.8%
avg views ÷ 9,380 subscribers
Avg views / post
1,580
58 posts measured
Reaction rate
0.88%
reactions ÷ views · ER floor
Posts in window
59
of 78 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. It is computed over the 56 of 58 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 29 August 2026
Posts held
78 (22 July 2026 – 29 August 2026)
Views total
91,422
Reactions total
773
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
29 Aug 2026, 07:56 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
Video runtime
24m 24s
Average length
3m 03s
Measured directly from 8 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.
Reaction mix
873 reactions across 66 posts, in 10 distinct kinds. The most used accounts for 71.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
628
71.9%
🔥
118
13.5%
❤🔥
47
5.38%
🤩
27
3.09%
👏
17
1.95%
🎉
15
1.72%
😍
10
1.15%
👍
6
0.687%
🥰
4
0.458%
💊
1
0.115%
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 73 of the 78 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 930 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 78 most recent posts we hold, published 22 July 2026 to 29 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.
🌟به زودی....
کمیته پژوهش ایفسا نشنال با همکاری تیم لوکال های همدان، لرستان و اهواز برگزار میکند:
🔬 نقشه راه پژوهش در داروسازی
پژوهش برای بسیاری از دانشجویان از یک سؤال ساده شروع میشود:
«از کجا باید شروع کنم؟»
قرار است در یک دوره آموزشی آنلاین، مسیر پژوهش را از نقطه شروع تا مراحل پایانی، قدمبهقدم دنبال کنیم؛ از آشنایی با روشهای پژوهش و جستجوی علمی تا نگارش پروپوزال و مقاله، تحلیل داده و مسیر انتشار و تبدیل پژ…
⭕️کمیته ارتقا حرفهای ایفسا، به مناسبت روز داروساز برگزار میکند:
🎊 از سری رویدادهای «داروساز من» 🎊
💊 چالشهای دیروز، امروز و فردای داروسازی
(با محوریت داروخانه)
داروسازی در دنیای واقعی، همیشه به سؤالاتی با یک پاسخ مشخص ختم نمیشود.
گاهی یک بیمار عصبانی است؛
گاهی پای حریم خصوصی در میان است؛
و گاهی داروساز باید در شرایطی تصمیم بگیرد که هیچ انتخابی کاملاً ساده و بیچالش نیست.
این بار قرار نیست فقط دربارهی این چال…
⭕️ گزارش دوره داروساز من
جلسه اول
💊داروسازی؛شغل یا حرفه
👨🏫مدرس: دکتر اسمعلی پور
📅تاریخ برگزاری:
جمعه ۶ شهریور ساعت ۱۸-۲۰
شرح عناوین:
▫️حرفه من داروسازی است نه شغل من
▫️آیا انسان میتواند اخلاق را از زندگیاش حذف کند؟
▫️تفاوت حرفه و شغل
▫️نظرسنجی گالوپ و رتبهبندی شغلها از نظر صداقت و پاکدامنی
▫️در حرفه، تجربه برپایه دانش و علم است.
▫️ارتباط ۳ اصطلاح: حرفه، حرفهمند، تعهد حرفهای
▫️تعهد حرفهای چیست؟
▫️تفاوت بیما…
💫سر رسیدیم!
ایفسا تایمز... سری سوم روی خط خبره!🔥
🗒این بار خبرا رو جور دیگهای میبینی، شفافتر، صریحتر و کاربردی تر...
💊از اخبار داغ حوزه دارو تا چالش های پیش رو!
با ما همراه باش تا ثابت کنیم آگاهی، بهترین سرمایهگذاری برای سلامت فرداست🫱🏻🫲🏻
#Be_The_Change
#ایفسا_خانواده_دانشجویان_داروسازی
____
💊 Telegram | LinkedIn | Instagram
💊 PR | Group | Youtube | Castbox
⭕️کمیته ارتقاء حرفهای ایفسا، به مناسبت روز داروساز برگزار میکند:
🎊 از سری رویدادهای «داروساز من»🎊
💊 داروسازی؛ شغل یا حرفه؟
داروساز بودن فقط به دانستن نام داروها، دوزها و تداخلاتشان خلاصه نمیشود؛
بخشی از حرفهای بودن این است که بدانیم بهعنوان یک داروساز، چه حقوقی داریم، چه مسئولیتهایی بر عهدهمان است و چطور میتوانیم بین این دو تعادل برقرار کنیم.
⚖️ سالها از مسئولیتها و وظایف داروساز گفتهایم؛
اما این بار م…
از هرکداممان که بپرسید «چرا داروسازی؟» یک جواب متفاوت میشنوید؛ یکی عاشق شیمی بود، یکی از خون میترسید، یکی رؤیای کشف دارویی بزرگ داشت و یکی هم فکر میکرد فقط قرار است اسم چندتا قرص را حفظ کند… چه خیال شیرینی! 😂💊
اما قصهی داروسازی خیلی قدیمیتر از ماست. از درمانگران اوستا که با گیاه و دارو به جنگ بیماری میرفتند، تا امروز که میان مولکولها، میکروسکوپها و ارلنها دنبال درمان میگردیم؛ ابزارها عوض شدهاند، اما هدف…
💊ویژهنامه روز داروساز نشریه «سیتالوگرام» تقدیم میکند!✨
به مناسبت روز داروساز، این ویژهنامه را به داستان داروسازی اختصاص دادهایم؛ از ریشههای این علم و میراث دانشمندانی چون رازی، تا تحولات امروز و آینده علم و سلامت.
🏛 صاحب امتیاز: انجمن علمی دانشکده داروسازی لرستان (ایفسا)
👨🏫 مشاور علمی: دکتر مجید پیرامون
👤 مدیرمسئول: صادق حاتمی لرستانی
🖋 سردبیر و ویراستار: فاطمه علیبلندی
💻 گرافیست: صدرا صبری
👥 اعضای هیئت تحر…
✨دومین نمایشگاه مجازی فارماآرت به مناسبت گرامیداشت روز داروساز با کمال افتخار و احترام تقدیم میکند:❤️
ما مفتخریم که در این رویداد ویژه، آثار هنری داروسازان خلاق و هنرمند کشورمان را که در گوشه و کنار این مرز و بوم به خلق زیباییها پرداختهاند، به نمایش بگذاریم. این هنرمندان با استعداد، نه تنها در عرصههای علمی و حرفهای خود درخشان هستند، بلکه با آثارشان دنیایی از احساسات و اندیشهها را به تصویر میکشند و مایهی افتخ…
روز داروساز مبارک💊✨
داروسازی، فقط کنار هم گذاشتن چند ماده و ساختن یک دارو نیست؛
قصهی ما، قصهی پیوند علم و خلاقیت، دانش و انسانیت است.
قصهی ساعتهایی که میان کتابها گذشت، ساختارهایی که بارها کشیدیم، نامهایی که حفظ کردیم و در نهایت فهمیدیم پشت هر دارو، یک داستان از علم و زندگی پنهان شده است. 🌿
به همین مناسبت، مسابقه «فارما کُد» رو راه انداختیم!🧪
قطعا شما هم برای یادگیری داروها، ساختارها، گیاهان دارویی و کلی مط…
ایفسا با همکاری دکتر آباد، مجموعهای از آزمونهای شبیهساز آزمون جامع داروسازی را برگزار میکند. 📚✨
💐 روز داروساز را به تمامی دانشجویان و داروسازان عزیز تبریک میگوییم.
💊آزمون های شبیه ساز آزمون جامع داروسازی 💊
این آزمونها طراحی شدهاند تا در فضایی نزدیک به شرایط آزمون جامع، دانش خود را ارزیابی کنید، مهارت مدیریت زمان را تقویت کنید و پیش از آزمون اصلی، نقاط قوت و مباحثی را که نیاز به مرور بیشتری دارند بهتر بشناسی…
روز داروساز| افتخار یک میراث ماندگار
از محمد بن زکریای رازی تا تلاشهای نسل امروز داروسازان ایرانی؛ یک مسیر کهن که با تلاش ساخته شده.
داروسازی در ایران همیشه با دانش، جستوجو و خدمت به انسان گره خورده است. 🧪💊
امروز، خانواده ایفسا به تمام داروسازان و دانشجویان داروسازی ایران تبریک میگوید؛
به آنهایی که این مسیر را ادامه میدهند و برای ساختن آیندهای بهتر تلاش میکنند.
روز داروساز مبارک؛
به افتخار گذشتهای که الهامب…
❤32❤🔥7🔥3
Showing the 12 most recent of 78 posts we hold for @IPhSAIran. 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
@IPhSAIran edited 1 post 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
18 August 2026
Most recent edit
18 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 37 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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.
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.
" فارمامدیکال 📞 pharmamedicall@ " @pharmamedicall · 38,922 Telegram ranks this channel #58 of 89 here — alongside 88 others — read 31 August 2026
داروشناسی پزشکی @medical_drugs1 · 52,134 Telegram ranks this channel #59 of 95 here — alongside 94 others — read 24 August 2026
فارماکولوژی @daruu_2020 · 32,516 Telegram ranks this channel #72 of 92 here — alongside 91 others — read 5 September 2026
آموزش نسخه خوانی @noskhe_daro · 47,821 Telegram ranks this channel #77 of 90 here — alongside 89 others — read 26 August 2026
صرفا نسخه‼️ @noooskhe · 49,305 Telegram ranks this channel #84 of 90 here — alongside 89 others — read 26 August 2026
This channel appears in 5 seed channels' Telegram-generated recommendation lists 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 4 September 2026 — this
entry's latest reading, not the date you are reading this.
“ایفسا (دانشجویان داروسازی ایران)” (@IPhSAIran), 9,380 subscribers as measured 4 September 2026. Telegram Register, tgregister.com/channel/IPhSAIran.
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.