Health & wellness — 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 4 October 2026 and assigned it the closest of 31 fixed categories, at 95% 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.
Growth
15 measurements spanning 53 days, net +149. 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 5,900–6,093 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
4 Nov 2026, 12:20
6,071
+8
1 Nov 2026, 16:57
6,063
+24
29 Oct 2026, 17:36
6,039
-11
26 Oct 2026, 17:05
6,050
+16
23 Oct 2026, 16:40
6,034
+12
21 Oct 2026, 01:48
6,022
+12
17 Oct 2026, 21:04
6,010
+33
14 Oct 2026, 16:56
5,977
-6
11 Oct 2026, 12:54
5,983
+11
4 Oct 2026, 22:57
5,972
+21
25 Sept 2026, 19:55
5,951
+19
17 Sept 2026, 14:39
5,932
-2
13 Sept 2026, 18:41
5,934
+12
12 Sept 2026, 06:22
5,922
no change
12 Sept 2026, 05:47
5,922
first reading
Engagement
34 posts held, back to 29 April 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 6 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
0.918%
avg views ÷ 6,071 subscribers
Avg views / post
55.7
7 posts measured
Reaction rate
13.8%
reactions ÷ views · ER floor
Posts in window
7
of 34 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.
What these figures were computed from
Window
Rolling 30 days · latest post in window 5 November 2026
Posts held
34 (29 April 2026 – 5 November 2026)
Views total
390
Reactions total
54
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
5 Nov 2026, 17:08 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
Photos
58
Videos
18
Links
32
Lifetime counters from Telegram’s own channel header, read 5 November 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.
Reaction mix
268 reactions across 32 posts, in 4 distinct kinds. The most used accounts for 28.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
76
28.4%
👍
66
24.6%
🥰
66
24.6%
😍
60
22.4%
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 32 of the 34 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 268 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 34 most recent posts we hold, published 29 April 2026 to 5 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 7 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
⚠️إلى طلاب سورية الأكابر👇⁉️
🌟اجعل تطبيق التيليجرام مصدرك الأول بالشروحات والنماذج الدراسية ...
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⬅️ كل ماعليك فعله الضغط على الرابط أدناه والإنضمام لقنواتنا:
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🎓 طلاب الصف التاسع، هذا المكان إلكم! 📚
هل تبحث عن كل ما يساعدك على التفوق والنجاح في شهادة الصف التاسع؟ 💯
انضموا إلى قناة تاسع لتجدوا كل ما تحتاجونه في مكان واحد:
📌 ملخصات ودروس مهمة
📌 حلول وأسئلة ونماذج امتحانية
📌 معلومات وملفات دراسية
📌 أخبار وقرارات رسمية
📌 كل جديد يخص طلاب الصف التاسع
👥 انضم إلى كروب الطلاب وشارك زملاءك واستفد من النقاشات: 🔗 https://t.me/Tasaa91
📢 تابع قناة تاسع ليصلك كل جديد: 🔗 https://t.me/Tasa…
الحلقة [06]: "منوم ليلة الامتحان".. رحلة للنوم العميق أم مسح مؤقت للذاكرة؟ 🛌💤
مع اقتراب موعد المادة وتراكم التوتر، يطير النوم من العين، ويبدأ البحث السريع عن حل منقذ: حبة "بنادول نايت"، مضاد هيستامين كلاسيكي، أو جرعة مضاعفة من الميلاتونين. لكن هل هذه الأدوية تضمن لك استيقاظا نشطاً للتقديم، أم أنها تطفئ دماغك فعليا داخل قاعة الامتحان؟ إليك الخلاصة الدقيقة المبنية على تحذيرات منظمة الغذاء والدواء (FDA) والأبحاث السرير…
الحلقة الخامسة | كذبة "حبة الذكاء".. طريقك للفل مارك ولا تدمير للسيستم؟ 🚀💊
أهلاً بكم يا شباب في أروقة "صيدلية الطالب". يسعدني أن نلتقي مجدداً لنستكمل رحلتنا في الوعي الصحي. اليوم سأشارككم نتائج أبحاثي وملاحظاتي حول ظاهرة خطيرة تنتشر بينكم بصمت في أوقات الضغط، وهي استخدام الأدوية المنشطة بهدف الدراسة.
دعونا نغوص في التفاصيل علمياً وعملياً:
1. الدافع النفسي ووهم التعزيز المعرفي (Cognitive Enhancement) 🧠✨
كثيراً ما أسم…
🌿 صيدلية الطالب | الحلقة الرابعة: «نار بالمعدة».. لما فنجان القهوة يقلب ضدك! ☕🔥
كم مرة صحيت مستعجل عالدوام، ضربت فنجان قهوة (أو كاسة شاي تقيلة) على معدة فاضية، ومع أول محاضرة حسيت بنار طالعة لحلقك؟
حرقة المعدة أو الارتجاع المريئي هو رفيق السكن غير المرغوب فيه لأغلب الطلاب.. فتعالوا نفهم شو القصة صيدلانياً وببساطة:
🔍 شو اللي عم يصير جوا؟
بين المريء والمعدة في عضلة عاصرة (مثل الباب الذكي)، وظيفتها تفتح للأكل وتسكّر فور…
بوصلة التخصص... من الحيرة إلى قيامة الشغف
مقدمة: على عتبات المستقبل
أهلاً بكم في هذه المرحلة الفاصلة من حياتكم. أعلم تماماً حجم الحيرة والقلق الذي يرافقكم الآن؛ فبين ضغوط المعدل، وتوقعات الأهل، والأحلام الشخصية، يبدو اختيار التخصص الجامعي وكأنه معركة مصيرية. لكنني هنا اليوم لأشارككم تجربة شخصية، علّها تضيء لكم جانباً مختلفاً من هذه الرحلة؛ جانب يخبركم أن الخطة "ب" قد تكون هي قدركم الأجمل.
التبويب الأول: حلم البدايات.…
Showing the 12 most recent of 34 posts we hold for @mgh_math25. 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 recorded as deleted after publishing
We recorded 3 posts on @mgh_math25 as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
4 November 2026
Most recent seen missing
5 November 2026
Median time before seen missing
14 hours
Seen missing in the last 30 days
3
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
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.
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.
مركز سوريا العلمي - تاسع @ssc_tasea · 25,446 Telegram ranks this channel #61 of 84 here — alongside 83 others — read 12 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 4 November 2026 — this
entry's latest reading, not the date you are reading this.
“˛ 𝗧𝗵𝗲 𝗣𝗵𝗮𝗿𝗺𝗮 𝗚𝘂𝗶𝗱𝗲 ⧞ .” (@mgh_math25), 6,071 subscribers as measured 4 November 2026. Telegram Register, tgregister.com/channel/mgh_math25.
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.