3 measurements spanning 7 days, net +3. 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 127–130 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 13:17
130
+3
9 Aug 2026, 02:02
127
no change
6 Aug 2026, 08:15
127
first reading
Engagement
20 posts held, back to 18 June 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 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
169.0%
avg views ÷ 130 subscribers
Avg views / post
220
8 posts measured
Reaction rate
1.11%
reactions ÷ views · ER floor
Posts in window
8
of 20 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 7 of 8 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 6 August 2026
Posts held
20 (18 June 2026 – 6 August 2026)
Views total
1,758
Reactions total
19
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
9 Aug 2026, 02:02 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.
Reaction mix
42 reactions across 16 posts, in 2 distinct kinds. The most used accounts for 97.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
41
97.6%
😍
1
2.38%
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 16 of the 20 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 20 most recent posts we hold, published 18 June 2026 to 6 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.
📖 علوم پایه فقط یک آزمون نیست؛ اولین چالش جدی دوران پزشکیه و دندان پزشکیه!
اگر هنوز نمیدونی از کجا شروع کنی، چه منابعی بخونی یا چطور برنامهریزی کنی، این پنل دقیقاً برای توئه.
🎯 قراره از تجربه دانشجوهایی بشنوی که همین مسیر رو با موفقیت پشت سر گذاشتن و با رتبههای برتر و استریت از آزمون علوم پایه عبور کردن.
تو این پنل یاد میگیری: ✅ چطور هوشمندانه درس بخونی، نه فقط بیشتر. ✅ چه منابعی واقعاً ارزش وقت گذاشتن دارن. ✅…
🎙️✨ دیگه لازم نیست ویسهای طولانی رو بشنوی و تایپ کنی!
اگه شما هم از اون دسته آدمهایی هستید که پیامهای صوتی طولانی رو ترجیح میدن بهصورت متنی بخونن، این معرفی مخصوص شماست 👇
🤖 ابزار امروز: Voicy | @voicybot
یک ربات تلگرامی رایگان و کاربردی که پیامهای صوتی، فایلهای صوتی و حتی ویدیو رو در کسری از ثانیه به متن تبدیل میکنه. کافیه اضافهاش کنید تا زیر هر ویس، متنش رو ببینید 🪄
🌟 چرا این ربات؟
🔹 رایگان و بدون نیاز …
😅 همهی ما توی دوران کارآموزی، حداقل یه خاطره داریم که با یادآوریش یا از خنده ریسه میریم، یا هنوزم دلمون میخواد زمین دهن باز کنه و قورتمون بده!
اون اشتباه بامزه، سوتی فراموشنشدنی یا لحظهی پراسترسی که هیچوقت از یادتون نمیره چی بوده؟ 🤭
✍️ برای چاپ در نشریه پویش، خاطرات تلخوشیرین دوران کارآموزیتون رو برای آیدی @Ftm_Fathi14 بفرستید.
شاید بزرگترین درسهای دوران تحصیل دقیقاً از همون اشتباههای کوچیک شروع شده باشن…
📌منابع آزمون دستیاری دندانپزشکی سال۱۴۰۶ (دوره ۴۱) اعلام شد.
📌تنها تغییر ایجاد شده در درس پریودانتیکس می باشد و فصول ۲۷ و ۴۶ و ۶۳ و ۶۴ و ۶۵ کارانزا نسبت به سال گذشته حذف شده است.
#آزمون_دستیاری_دندانپزشکی
@aviddent
🌟 درخشش عضو فعال EDO دانشجویی دانشکده دندانپزشکی دانشگاه علوم پزشکی بابل، جناب آقای سعید قورچائی
📝با خوشحالی و افتخار، انتشار مقاله علمی
The Persian Version of the Social Participation Questionnaire: Translation, Cross‑Cultural Adaptation, and Psychometric Evaluation Using CATPCA
را به جامعه علمی دانشگاه تبریک میگوییم.
📌این پژوهش با ترجمه و بومیسازی پرسشنامه مشارکت اجتماعی (SPQ) و بررسی دقیق روایی و پایایی آن در …
⭕️مقایسه مختصر بین ژینژیویت و پریودنتیت:
🔹ژینژیویت فقط التهاب لثهست و کاملاً قابل برگشته؛ اما پریودنتیت یعنی آسیب به بافتهای نگهدارنده دندان و تحلیل استخوان که دیگه برگشتپذیر نیست!!!
🔹در ژینژیویت معمولاً فقط قرمزی، تورم و خونریزی داریم، ولی در پریودنتیت پاکت لثه، تحلیل، لق شدن دندان و جرم زیرلثهای هم دیده میشه.
🔹عامل اصلی هر دو، پلاک و جرم هست؛ با این تفاوت که پریودنتیت بیشتر تحتتأثیر ژنتیک، تغذیه نامناسب و…
⚜سلسله پادکست های DENT TALK ⚜
🦷 در این قسمت از پادکست, میزبان یکی از اساتید محترم جراحی دهان، فک و صورت بودیم؛ "جناب آقای دکتر رحمانی"
‼️از مسیر ورود به جراحی تا سختترین لحظات اتاق عمل، از واقعیتهای رزیدنتی تا آینده این تخصص…
✨گفتوگویی صمیمی، واقعی و الهامبخش که شنیدنش برای هر دانشجوی دندانپزشکی ضروریه
00:00 معرفی🎤
01:27 عامل و انگیزه انتخاب این رشته 💥
02:17 نقطه عطف این رشته ⚡️
3:13 ساختار دوره تخصص جراحی 👨…
🦷کمیته دانشجویی توسعه آموزش پزشکی (EDO) دانشکده دندانپزشکی دانشگاه علوم پزشکی بابل برگزار میکند:
💠دومین جلسه CBL(case base learning)💠
◀️ case selection
در بيماران نیازمند درمان ریشه
☑این جلسه برای افرادی هست که میخوان تجارب و دانش بالینی خودشون رو درقالب برخورد با کیس های بالینی بیشتر کنند و دندانپزشکان بهتری شوند😊
✅در این جلسه شما با کیس های مختلف اندو مواجه میشید
✅ با علائمشون آشنا میشید و نکات مهم در شرح حال …
❤4
Showing the 12 most recent of 20 posts we hold for @edo_dentbabol. 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
Citation-graph rank — 170,113 of 1,480,944entries 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.
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 4 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.
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 13 August 2026 — this
entry's latest reading, not the date you are reading this.
“کمیته دانشجویی توسعه آموزش دانشکده دندانپزشکی بابل” (@edo_dentbabol), 130 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/edo_dentbabol.
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.
