Telegram RegisterThe public register of Telegram
Telegram profile photo for 𝚂𝚌𝚒𝚎𝚗𝚝𝚒𝚏𝚒𝚌 𝙰𝚛𝚝𝚒𝚌𝚕𝚎𝚜

Channel

𝚂𝚌𝚒𝚎𝚗𝚝𝚒𝚏𝚒𝚌 𝙰𝚛𝚝𝚒𝚌𝚕𝚎𝚜

@iQscin

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

50,355subscribers

+70 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1001695136614
TypeChannel
Username@iQscin
DescriptionScience Research and helping researchers
CreatedBetween 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live18 September 2026
Measurements held30
Confirmed unchanged1 time, most recently 18 September 2026
On Telegramt.me/iQscin

Topic

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 9 September 2026 and assigned it the closest of 31 fixed categories, at 53% 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

50,21550,36350,2897 August 2026 — 50,285 subscribers8 August 2026 — 50,266 subscribers9 August 2026 — 50,293 subscribers10 August 2026 — 50,281 subscribers11 August 2026 — 50,274 subscribers12 August 2026 — 50,260 subscribers14 August 2026 — 50,245 subscribers15 August 2026 — 50,235 subscribers16 August 2026 — 50,224 subscribers17 August 2026 — 50,215 subscribers19 August 2026 — 50,224 subscribers20 August 2026 — 50,240 subscribers22 August 2026 — 50,268 subscribers23 August 2026 — 50,257 subscribers25 August 2026 — 50,263 subscribers26 August 2026 — 50,268 subscribers27 August 2026 — 50,300 subscribers29 August 2026 — 50,297 subscribers30 August 2026 — 50,303 subscribers31 August 2026 — 50,298 subscribers1 September 2026 — 50,292 subscribers2 September 2026 — 50,290 subscribers3 September 2026 — 50,293 subscribers4 September 2026 — 50,341 subscribers8 September 2026 — 50,363 subscribers11 September 2026 — 50,356 subscribers13 September 2026 — 50,363 subscribers14 September 2026 — 50,358 subscribers16 September 2026 — 50,350 subscribers18 September 2026 — 50,355 subscribers50,3557 August 202618 September 2026
30 measurements spanning 42 days, net +70. 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 50,193–50,385 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 30
Measured (UTC)SubscribersChange
18 Sept 2026, 17:1750,355+5
16 Sept 2026, 09:0050,350-8
14 Sept 2026, 16:1650,358-5
13 Sept 2026, 02:2050,363+7
11 Sept 2026, 02:2150,356-7
8 Sept 2026, 02:3750,363+22
4 Sept 2026, 21:1850,341+48
3 Sept 2026, 06:1750,293+3
2 Sept 2026, 00:0950,290-2
1 Sept 2026, 02:1750,292-6
31 Aug 2026, 02:0450,298-5
30 Aug 2026, 04:2450,303+6
29 Aug 2026, 06:3450,297-3
27 Aug 2026, 08:1550,300+32
26 Aug 2026, 06:2750,268+5
25 Aug 2026, 03:4250,263+6
23 Aug 2026, 20:5750,257-11
22 Aug 2026, 05:0850,268+28
20 Aug 2026, 19:5350,240+16
19 Aug 2026, 21:1250,224first reading

Engagement

111 posts held, back to 2 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 91 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
3.60%
avg views ÷ 50,355 subscribers
Avg views / post
1,810
53 posts measured
Reaction rate
0.33%
reactions ÷ views · ER floor
Posts in window
53
of 111 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 32 of 53 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 19 September 2026
Posts held111 (2 August 202619 September 2026)
Views total96,078
Reactions total219
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken21 Sept 2026, 16:58 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
2,650
Videos
13
Links
2,850

Lifetime counters from Telegram’s own channel header, read 21 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Reaction mix

368 reactions across 75 posts, in 8 distinct kinds. The most used accounts for 80.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
29580.2%
👍4311.7%
🔥205.43%
41.09%
👏30.815%
🏆10.272%
👎10.272%
😍10.272%

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 77 of the 111 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 368 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 111 most recent posts we hold, published 2 August 2026 to 19 September 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

19 Sept 2026, 16:18 UTC≈1,240 viewsread 21 September 2026

التأكد من إبراز الأفكار المبتكرة والتأكيد على مدى رصانتها. 💡 توجيه هندسي: يضمن هذا الفصل المنهجي تفادي السطحية والهلوسة، حيث يتكفل Gemini Notebook بالمورد المرجعي الدقيق والاسترجاع، بينما يتكفل Claude بالتدقيق المنطقي وإثراء الصياغة النقدية.

19 Sept 2026, 16:18 UTC≈1,170 views4 reactionsread 21 September 2026

🟣 اهم الأوامر لسير العمل الأكاديمي (Gemini Notebook + Claude) يعتمد نجاح هذا المسار البحثي المكون من 6 خطوات على توزيع الأدوار المهيكلة (Role Allocation) واستخدام أحدث تقنيات هندسة الأوامر مثل: التفكير السلسلي (Chain-of-Thought)، التقييد الهيكلي (Structural Constraints)، والتحليل النقدي الخصم (Red Teaming / Devil's Advocate). ✅ يقوم سير العمل على التكامل بين Gemini Notebook لمرحلة التجميع والربط المرجعي المباشر، وCla

4

19 Sept 2026, 16:18 UTC703 views3 reactionsread 21 September 2026

🔵 لتطبيق سير العمل والأوامر التوجيهية على أوراقك البحثية، يمكنك اتباع الخطوات التالية: رفع الأوراق البحثية كـ "مصادر" (Sources): قم برفع ملفات PDF أو المستندات الخاصة بمراجعتك البحثية إلى كشكول العمل (Gemini Notebook)، حتى تصبح هي القاعدة المرجعية المعتمدة للتحليل. تطبيق أمر "مدقق الأبحاث" (Research Auditor): انسخ الأمر الأول وضعه في خانة المحادثة مع الكشكول: "قم بتحليل كل مصدر في هذا الكشكول واستخراج أهم النتائج، وا

3

19 Sept 2026, 16:18 UTC832 viewsread 21 September 2026

‼️ دليلك الأكاديمي المتقدم: كيف تحول عشرات الأبحاث والمصادر إلى محتوى علمي محكم باستخدام متزامن بين Gemini NotebookLM و Claude 🟠إلى زملائي الباحثين وطلبة الدراسات العليا، نستعرض في هذا الدليل خطة عمل مبتكرة لتحويل الأبحاث المتراكمة إلى محتوى متكامل باستخدام أدوات الذكاء الاصطناعي "Gemini" و"Claude". تبدأ العملية بتوظيف "Gemini" لفحص المصادر واستخراج الأفكار المترابطة والفجوات المعرفية ضمن ملخص بحثي منظم. تليها مرحلة

19 Sept 2026, 07:24 UTC≈1,030 views12 reactionsread 21 September 2026

‼️إذا كنت ما تزال تتعامل مع Literature Review بالطريقة التقليدية: تفتح Google Scholar، تجمع عشرات الروابط، تفتح عشرات التبويبات، ثم تحاول معرفة ما الذي يدعم ماذا… فقد حان الوقت لإعادة تصميم طريقة عملك. 🟡 الذكاء الاصطناعي لا يختصر البحث العلمي إلى (اكتب لي Literature Review)، بل يمكن استخدامه لبناء سير عمل بحثي أكثر تنظيماً: من صياغة السؤال، إلى اكتشاف الأدبيات، ثم تحليل العلاقات بين الدراسات، والتحقق من سياق الاستشها

10👍2

19 Sept 2026, 07:24 UTC794 views4 reactionsread 21 September 2026

‼️ مجموعة اوامر prompts احترافية لاعداد ورقة علميةمتقنة، احفظها لديك لاستخدامها بشكل مستمر . 🔸 مع التطور الحالي في هندسة الأوامر (Prompt Engineering) خلال 2026، أصبحت النماذج اللغوية لا تستجيب بصيغتها الحالية تُعد Prompts تقليدية (Basic Prompts). لذلك يتم تطويرها بشكل مستمر وبشكل أفضل عند استخدام: Role Prompting Chain-of-Thought Prompting Structured Output Prompting Evidence-based Reasoning Comparative Analysis Gap T

4

19 Sept 2026, 07:23 UTC≈1,090 views4 reactionsread 21 September 2026

‼️ كيف تصيغ وتكتب أمر prompt للحصول على نتائج ممتازة وأكثر دقة ❓ هذا هو السؤال الاكثر شيوعاً من قبل متابعينا الافاضل. (تجد نسخة باللغة الانجليزية في التعليقات)👇 🔸 تعال معي بعطيك السر في كتابة الاوامر prompts وراح تشكريني بعدين 😊 ✅ معظم الباحثين لا يعانون من ضعف الذكاء الاصطناعي بل من ضعف كتابة الأوامر. ⁉️ نفس الأداة، ونفس السؤال، لكن باحثًا يحصل على إجابة ممتازة، وآخر يحصل على إجابة سطحية ومليئة بالأخطاء. لماذا؟

4

13 Sept 2026, 10:22 UTC≈2,760 views18 reactionsread 21 September 2026

‼️أول ورقة علمية نشرتها في مجلة ذات تأثير عالي ، كتبتها بطريقة المحاكاة Academic writing by simulation method ، كنت في وقتها في حيرة كبيرة ، تعلمت الطريقة من احد الاصدقاء معي في university of sousse ، الصراحة كانت خطوة تعادل الف خطوة تعلم ، واليك الطريقة 👇 🟠 للمبتدئين ما هو أسلوب المحاكاة (simulation) في الكتابة الأكاديمية؟ 1️⃣ الجانب الاول هو أن أهم اسباب التميز في الكتابة الأكاديمية يكمن في "المحاكاة" بمعنى أن هن

11👍4🔥2😍1

Showing the 12 most recent of 111 posts we hold for @iQscin. 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 1 registered channel — 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.

Channels Telegram recommends alongside this one

Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.

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@manthomah1443 · 25,318
#79
مكتبة قسم التاريخ PDF📚🪙
@TV_SYRIA · 5,309
#80
خادم العلم والمعرفة
@thesesdz2 · 38,001
#81
وزارة المالية العراقية
@mofiraq · 54,385
#82
( تخاطب ) VOCAL
@Kianspecialeducation · 10,497
#83
مخزن الكتب
@books_dm · 45,521
#84
تكوين العالم المؤصِّل
@muaasel · 3,238
#85
مكتبة عمر عكاشة
@omerokasha · 22,839
#86
المكتبة الهندسية الشاملة
@MEltonopy · 134,880
#87
Sharif Sheikh Ahmed
@sharifshahmed · 11,042
#88
The Library of the Newest ever Books
@SafiNewestEverBooks · 1,130 (as read 25 August 2026)
#89

Read from Telegram’s recommendation API, most recently 25 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.

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.

English
@English2020free · 222,935
Telegram ranks this channel #25 of 72 here — alongside 71 others — read 11 August 2026
وظائف ومنح
@WazafnyHaln · 23,942
Telegram ranks this channel #29 of 64 here — alongside 63 others — read 17 September 2026
Fedniy . فدني
@fedniy · 248,827
Telegram ranks this channel #40 of 73 here — alongside 72 others — read 10 August 2026
Engli-Vision Community
@englivisionteam · 62,126
Telegram ranks this channel #45 of 83 here — alongside 82 others — read 22 August 2026
IELTS with Ahmed Hassan
@IeltswithAhmed · 22,266
Telegram ranks this channel #56 of 85 here — alongside 84 others — read 21 September 2026
كتب إدارة الموارد البشرية
@HRM2017 · 23,586
Telegram ranks this channel #56 of 87 here — alongside 86 others — read 18 September 2026
Truescho
@truescho · 92,671
Telegram ranks this channel #60 of 80 here — alongside 79 others — read 16 August 2026
منح دراسية وتدريب
@applyscholars · 49,358
Telegram ranks this channel #63 of 75 here — alongside 74 others — read 25 August 2026
Eduhub21.com
@eduhub_21 · 54,545
Telegram ranks this channel #66 of 82 here — alongside 81 others — read 23 August 2026

This channel appears in 9 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 18 September 2026 — this entry's latest reading, not the date you are reading this.

“𝚂𝚌𝚒𝚎𝚗𝚝𝚒𝚏𝚒𝚌 𝙰𝚛𝚝𝚒𝚌𝚕𝚎𝚜” (@iQscin), 50,355 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/iQscin.

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.