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 (1 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. 1 of the 4 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 16 comparable posts for this entry, running 27 July 2026 to 7 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 @PulseIAS. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_copy, 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.
33 measurements spanning 43 days, net -266. 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 14,361–14,707 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)
Subscribers
Change
18 Sept 2026, 12:36
14,401
-10
16 Sept 2026, 05:37
14,411
-8
14 Sept 2026, 12:17
14,419
-10
12 Sept 2026, 20:20
14,429
-8
10 Sept 2026, 20:16
14,437
-28
7 Sept 2026, 16:19
14,465
-22
4 Sept 2026, 18:20
14,487
-4
3 Sept 2026, 05:55
14,491
-6
2 Sept 2026, 00:05
14,497
-5
1 Sept 2026, 01:48
14,502
-3
30 Aug 2026, 21:54
14,505
-7
30 Aug 2026, 00:43
14,512
+2
29 Aug 2026, 02:04
14,510
-5
28 Aug 2026, 04:47
14,515
-3
27 Aug 2026, 05:08
14,518
-4
26 Aug 2026, 04:22
14,522
-6
25 Aug 2026, 03:32
14,528
-2
23 Aug 2026, 20:55
14,530
-10
22 Aug 2026, 07:16
14,540
-6
20 Aug 2026, 22:34
14,546
first reading
Engagement
55 posts held, back to 27 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 52 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
2.06%
avg views ÷ 14,401 subscribers
Avg views / post
296
19 posts measured
Reaction rate
0.358%
reactions ÷ views · ER floor
Posts in window
19
of 55 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 4 of 19 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 2 September 2026
Posts held
55 (27 July 2026 – 2 September 2026)
Views total
5,628
Reactions total
5
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
2 Sept 2026, 18:35 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
25 reactions across 20 posts, in 3 distinct kinds. The most used accounts for 88.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
22
88.0%
👍
2
8.00%
🔥
1
4.00%
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 21 of the 55 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 25 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 55 most recent posts we hold, published 27 July 2026 to 2 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.
How NMP Works? Video coming tomorrow at 11:11 AM
🔥 Daily Mains Targets
🔥 Daily 1-Pager Notes on DARE Sheets [100% PYQ Themes]
🔥 Daily Evaluation [Those who submit in 24 Hrs] to inclucate Discipline
with [LIVE] Mentorship Sessions
This is how your Get Mains Ready 😊
Note Making Programme (NMP)
Learn the Art of Making 1-Pager Notes on our DARE Sheets
First of its Kind for UPSC Mains 🔥🔥
DISCIPLINE | CONSISTENCY | ACTIVE RECALL
This is How You get Mains Ready and not by Feeding More Content
Indian Agriculture starts from 9 Sept.
Enrol Now: https://www.pulseias.com/learn/upsc-mains-note-making-indian-agriculture
There are many Queries coming up. How this programme will run? Difference with CheckMate and CheckMate+
Will address all those queries in an another video.
Note Making Programme (NMP)
Learn the Art of Making 1-Pager Notes on our DARE Sheets
Check the Sample DARE Sheets of Governance
👆👆
First of its Kind for UPSC Mains 🔥🔥
Enrol Now: https://www.pulseias.com/learn/upsc-mains-note-making-indian-agriculture
Note Making Programme (NMP)
Learn the Art of Making 1-Pager Notes on our DARE Sheets
First of its Kind for UPSC Mains 🔥🔥
Indian Agriculture starts from 9 Sept.
Enrol Now: https://www.pulseias.com/learn/upsc-mains-note-making-indian-agriculture
LOWEST PRICE for First 100 Students.
Use Coupon Code: NMP (20% Discount)
Another Flagship Programme and First of its Kind for UPSC Mains !!
Learn to Make your 1-Pager Notes with the Team Behind CheckMate under the guidance of Amit Mangtani Sir 🔥🔥
Only 100 Seats in the First Batch as this will be [Live].
Launching Tomorrow at 11:11 AM 🤝
More than 85% Direct Hits in Mains 2026 ONLY from a SINGLE SOURCE.
(No Test Series or No Full Mock Tests or No Current Affairs or No Other Resource) -> Only from CHECKMATE [1-Pager Mains Notes] 🔥🔥
HIGHEST in the INDUSTRY making CheckMate as the UNDISPUTED LEADER in Mains Notes. 🏆
CheckMate your Mains with the Ultimate 1-Pager Mains Notes 🔥🔥
Showing the 12 most recent of 55 posts we hold for @MentorsHut. 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
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.
theIAShub @theiashub · 38,801 Telegram ranks this channel #11 of 81 here — alongside 80 others — read 31 August 2026
CSAT - by Sunya IAS @CsatSunyaIAS · 51,343 Telegram ranks this channel #16 of 84 here — alongside 83 others — read 25 August 2026
Free Study Materials @upsc_free_study_materials_pdf · 26,638 Telegram ranks this channel #32 of 58 here — alongside 57 others — read 12 September 2026
Hornbill Forestry 🌱 IFoS 2026 @forestryopt · 32,831 Telegram ranks this channel #38 of 72 here — alongside 71 others — read 19 September 2026
UPSC Notes @Upsc_notessss · 26,203 Telegram ranks this channel #41 of 62 here — alongside 61 others — read 12 September 2026
UPSC CSE Why @csewhy · 42,910 Telegram ranks this channel #41 of 73 here — alongside 72 others — read 29 August 2026
TARGET UPSC by Dr.Sudarshan Lodha (AIR 571 ) @target30upsc · 73,651 Telegram ranks this channel #44 of 95 here — alongside 94 others — read 19 August 2026
SuperKalam IAS @superkalam · 39,831 Telegram ranks this channel #48 of 75 here — alongside 74 others — read 30 August 2026
UPSC society mains @upsc_society_gs · 32,097 Telegram ranks this channel #50 of 87 here — alongside 86 others — read 5 September 2026
Rau's IAS Study Circle (Since 1953) @rausias1953 · 38,682 Telegram ranks this channel #50 of 74 here — alongside 73 others — read 31 August 2026
Rishav Sharma -PWOnlyIAS @rishavsharmasirpw · 122,084 Telegram ranks this channel #51 of 69 here — alongside 68 others — read 14 August 2026
UPSCPrep.com @UPSCprepIAS · 201,763 Telegram ranks this channel #51 of 82 here — alongside 81 others — read 11 August 2026
KAVACH - GS Foundation 2028 @sunyaiasgs · 29,257 Telegram ranks this channel #53 of 69 here — alongside 68 others — read 8 September 2026
Current Affairs by Prithu @saurabhPolity · 23,332 Telegram ranks this channel #55 of 80 here — alongside 79 others — read 18 September 2026
VK IAS- prelims (UPSC highlights) @upschighlights · 55,147 Telegram ranks this channel #63 of 87 here — alongside 86 others — read 23 August 2026
Convert IAS - Official @Convert_IAS · 135,525 Telegram ranks this channel #64 of 91 here — alongside 90 others — read 13 August 2026
Enlight IAS (Official) @EnlightIAS8_official · 136,195 Telegram ranks this channel #65 of 70 here — alongside 69 others — read 13 August 2026
UPSC plan B update @upsc_plan · 31,147 Telegram ranks this channel #72 of 87 here — alongside 86 others — read 6 September 2026
Sunya IAS - Sociology @sociology_sunyaias · 25,647 Telegram ranks this channel #73 of 87 here — alongside 86 others — read 13 September 2026
Environment & Ecology UPSC prelims mains @Upsc_4_environment · 29,997 Telegram ranks this channel #73 of 88 here — alongside 87 others — read 7 September 2026
OnlyIAS Nothing Else @onlyiasnothingelse · 207,348 Telegram ranks this channel #73 of 79 here — alongside 78 others — read 11 August 2026
UPSC Art and culture @upsc_art_and_culture · 28,117 Telegram ranks this channel #74 of 85 here — alongside 84 others — read 9 September 2026
ForumIASOfficial @forumiasofficial · 29,645 Telegram ranks this channel #77 of 80 here — alongside 79 others — read 8 September 2026
UPSC IR ( MINDMAPS) @UPSC_irmindmaps_di_mains_prelims · 46,166 Telegram ranks this channel #77 of 89 here — alongside 88 others — read 27 August 2026
This channel appears in 27 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. 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.
“MentorsHut (Amit Mangtani)” (@MentorsHut), 14,401 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/MentorsHut.
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.