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 10 September 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 why it has no browse page of its own yet.
Growth
33 measurements spanning 42 days, net +2,051. 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 13,196–15,863 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)
Subscribers
Change
17 Sept 2026, 21:41
15,555
+66
15 Sept 2026, 16:00
15,489
+20
14 Sept 2026, 02:38
15,469
+25
12 Sept 2026, 06:37
15,444
+35
10 Sept 2026, 00:56
15,409
+110
6 Sept 2026, 18:15
15,299
+189
4 Sept 2026, 06:16
15,110
+21
2 Sept 2026, 20:56
15,089
+39
1 Sept 2026, 22:15
15,050
+36
31 Aug 2026, 23:17
15,014
+41
30 Aug 2026, 23:04
14,973
+131
29 Aug 2026, 20:16
14,842
+39
28 Aug 2026, 22:44
14,803
+31
27 Aug 2026, 20:04
14,772
+37
26 Aug 2026, 17:42
14,735
+33
25 Aug 2026, 14:06
14,702
+49
24 Aug 2026, 11:05
14,653
+85
22 Aug 2026, 22:04
14,568
+33
21 Aug 2026, 11:47
14,535
+69
20 Aug 2026, 11:33
14,466
first reading
Engagement
99 posts held, back to 3 August 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 42 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.68%
avg views ÷ 15,555 subscribers
Avg views / post
1,510
6 posts measured
Reaction rate
1.26%
reactions ÷ views · ER floor
Posts in window
6
of 99 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 24 August 2026
Posts held
99 (3 August 2026 – 24 August 2026)
Views total
9,030
Reactions total
114
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
25 Aug 2026, 15:49 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
16h 29m
Average length
1h 49m
Measured directly from 9 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
1,836 reactions across 85 posts, in 28 distinct kinds. The most used accounts for 70.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,293
70.4%
🔥
194
10.6%
👍
80
4.36%
😭
75
4.08%
🥰
37
2.02%
😡
21
1.14%
😢
17
0.926%
❤🔥
16
0.871%
👏
16
0.871%
🤩
15
0.817%
⚡
10
0.545%
👎
10
0.545%
💘
8
0.436%
😱
7
0.381%
👌
6
0.327%
💯
6
0.327%
🍓
5
0.272%
😁
3
0.163%
😘
3
0.163%
🏆
2
0.109%
8 further kinds
12
0.654%
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 85 of the 99 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 1,836 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 99 most recent posts we hold, published 3 August 2026 to 24 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.
🔬 Qabas Research Initiative | Recruitment
We’re looking for 2 experienced researchers to join our research team:
1- 👨⚕️ Lecturer / Associate Professor – Ophthalmology
• Supervision of a Primary Study
• Responsible for Ethical Approval procedures
2- 📚 Research Supervisor – Systematic Review
• Scientific supervision and follow-up of an SR project
Requirements:
• Previous research experience is required for both ro…
السلام عليكم ورحمة الله وبركاته
أهلًا وسهلًا بيكم في Meta-analysis Course | Qabas Research Initiative 🔬
حابين نوضح لحضراتكم نظام الكورس بالكامل، خصوصًا للمشتركين الجدد:
📚 الكورس يتكون من 4 محاضرات + 2 Assignments
أولًا: المحاضرات الأولى والـAssignment الأول
المحاضرتان الأولى والثانية تم تقديمهما بالفعل، ولذلك مطلوب من المشتركين الجدد:
* 🎥 مشاهدة المحاضرتين.
* 📝 حل وتسليم Assignment 1.
🔗 Lecture 1: https://youtu.b…
السلام عليكم ورحمة الله وبركاته
تنبيه مهم بخصوص محاضرتي الMeta-analysis المتبقيتين:
أوضح د. عبدالله عباس أن المحاضرتين المتبقيتين مكملتان للمحاضرتين السابقتين، وبالتالي الحضور فيهما إجباري لمشتركي الدفعة الأساسية.
وبناءً على ذلك، تم زيادة الغيابات المسموحة تقديرًا لظروف المشتركين:
* 🔹 Track B: مسموح بـ3 غيابات.
* 🔹 Track A: مسموح بـ6 غيابات.
📌 توضيح بخصوص شهادة الـMeta-analysis Course:
الـFinal Assignment الخاص …
السلام عليكم ورحمة الله وبركاته
🔹 رابط حضور المحاضرة على Microsoft Teams:
https://teams.microsoft.com/meet/33175020305782?p=KR1nWUerBj8ydCJNuX
رابط البث المباشر متاح ومستقر بإذن الله
https://www.youtube.com/live/2SWcz_quIMc?si=M0Scxm6zwmVfyJ_T
في انتظاركم جميعاً❤️🌹
📢 Meta-analysis Course | Qabas Research Initiative 🔬
خطوة جديدة في رحلة قبس 🤍
بعد تقديم د. عبدالله عباس محاضرتين و2 Assignments، أصبح الـ Meta-analysis Course متاحًا بشكل مستقل بشهادة مستقلة 🎓
📚 4 Lectures + 4 Assignments
👨🏫 Dr. Abdullah Abbas
📝 Practical application & Assignment review
🎯 Final course exam
📅 Remaining Lectures: 25 & 26 August
⏰ 10 PM (Egypt Time)
🎓 Certificate Requirements:
• Complete the requi…
السلام عليكم ورحمة الله وبركاته
نعتذر عن التأخير
تفريغات و محاضرات Phase 5 بقت متاحه الان
لو حابين تراجعوا المحاضرات أو ترجعوا لأي نقطة اتشرحت، هتلاقوا التفريغات هتسهل عليكم جدًا.
بالتوفيق للجميع 🌹❤️
#Toolkits 🧰
Here are the materials shared by Mostafa Meshref :
for the American Board Certified Doctors for Egypt session
• Session Announcement
• Registration Link
❤2
Showing the 12 most recent of 99 posts we hold for @Qabas00000. 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
@Qabas00000 edited 4 posts 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
9 August 2026
Most recent edit
24 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 6 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 17 September 2026 — this
entry's latest reading, not the date you are reading this.
“Qabas - قَـبَـس” (@Qabas00000), 15,555 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/Qabas00000.
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.