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 the other topics.
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 in near-verbatim form on 1 other registered channel. This entry also forms a group of 2 channels linked by matching posts. 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)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
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. None of the 1 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 44 comparable posts for this entry, running 3 June 2026 to 6 November 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).
Of the group of 2 channels, the one whose matching posts we hold earliest is @iassatyashodhak. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_copy, last confirmed 11 November 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.
Channels linked by matching posts
This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim 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.
61 measurements spanning 94 days, net -152. 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 10,157–10,356 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 61
Measured (UTC)
Subscribers
Change
9 Nov 2026, 15:56
10,180
-3
8 Nov 2026, 04:52
10,183
-4
7 Nov 2026, 00:19
10,187
-1
5 Nov 2026, 23:19
10,188
-5
5 Nov 2026, 00:56
10,193
-3
3 Nov 2026, 23:21
10,196
-1
3 Nov 2026, 00:56
10,197
-3
2 Nov 2026, 03:59
10,200
-3
1 Nov 2026, 04:40
10,203
-2
31 Oct 2026, 01:19
10,205
-1
29 Oct 2026, 22:09
10,206
-6
28 Oct 2026, 19:51
10,212
-1
27 Oct 2026, 19:06
10,213
-2
26 Oct 2026, 15:15
10,215
-6
25 Oct 2026, 13:45
10,221
-1
23 Oct 2026, 12:17
10,222
-2
22 Oct 2026, 13:19
10,224
-2
21 Oct 2026, 09:16
10,226
+1
20 Oct 2026, 07:45
10,225
-3
19 Oct 2026, 09:07
10,228
first reading
Engagement
128 posts held, back to 3 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 54 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
4.74%
avg views ÷ 10,180 subscribers
Avg views / post
483
23 posts measured
Reaction rate
0.706%
reactions ÷ views · ER floor
Posts in window
23
of 128 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 6 of 23 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 7 November 2026
Posts held
128 (3 June 2026 – 7 November 2026)
Views total
11,107
Reactions total
28
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
10 Nov 2026, 22:09 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
≈3,500
Videos
≈151
Links
≈3,600
Lifetime counters from Telegram’s own channel header, read 10 November 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.
Video runtime
25s
Average length
25s
Measured directly from 1 video 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
459 reactions across 51 posts, in 11 distinct kinds. The most used accounts for 79.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
365
79.5%
👏
29
6.32%
💯
20
4.36%
👍
15
3.27%
🙏
9
1.96%
👀
7
1.53%
👌
5
1.09%
😁
3
0.654%
🔥
2
0.436%
🤔
2
0.436%
🫡
2
0.436%
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 57 of the 128 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 459 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 128 most recent posts we hold, published 3 June 2026 to 7 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 23 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).
Hello folks, since last 4 months I'm almost inactive on channel. Meanwhile I prepared for NEETPG 2026 and yesterday first round allotment list declared. I got MD MEDICINE at BJ medical college and sasoon hospital pune.
This channel literally helped me keeping my mind in sound state. personally speaking this space introduced me to my altogether different version. Thank you very much for being there. So many things to …
⛔️ ADVICE ⛔️ ::
Friends, if you're struggling with answer-writing inertia, remember you're not alone. Few are just reading the mains content repeatedly to avoid getting harshly evaluated by evaluator.
I'll tell you a simple strategy 👇
1- create your peer group (if not possible then write individually)
2 - Take last 10 years mains questions (subject wise).
3 - write them daily (atleast 5 questions) and discuss t…
Different types of Carbon:
1. Green Carbon: Carbon stored in terrestrial plants.
2. Blue Carbon: Carbon stored in ocean plants and sediments.
3. Purple Carbon: Carbon captured through the air or industrial emissions.
4. Teal Carbon: Carbon stored in freshwater and wetland environments
1. Black Carbon: Carbon released through the burning of fossil fuels.
2. Brown Carbon: Carbon released by incomplete combustion…
Different types of Methanol (Carbon Footprint & Source)
1. Gray Methanol (Natural Gas-based): Produced from fossil natural gas via steam methane reforming (SMR). It is currently the most common type of commercial methanol but emits significant CO₂.
2. Brown Methanol (Coal-based): Produced by gasifying coal; it has a high carbon footprint and offers minimal to no greenhouse gas reductions.
3. Blue Methanol (Low-ca…
Q.) Consider the following statements about Mishmi takin:
1. It is found in Ladakh and Himachal Pradesh.
2. It is protected under the Schedule I of the Wild Life (Protection) Act of 1972.
3. It is listed as Vulnerable in the IUCN's Red List of Threatened Species.
Q.) Bovista Colorata has been recently identified from Arunachal Pradesh. It is a species of:
A.) Butterfly.26%
B.) Fish.17%
C.) Mushroom.46%
D.) Mangrove.11%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Showing the 12 most recent of 128 posts we hold for @EnvirForUPSC. 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.
Polls
The 6 most recent of 51 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.
Q.) "The Turquoise Nexus Initiative (TNI)", sometimes in news, is an initiative primarily aimed at:
A.) promoting sustainable marine and coastal ecosystems through the expansion of the blue economy.20%
B.) integrating food security, water management, climate adaptation into national policies.41%
C.) creating a global regulatory framework for deep-sea mining and rare-earth mineral extraction.30%
D.) establishing binding country-level targets to phase out agricultural methane emissions.9%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 128 most recent posts we hold, published 3 June 2026 to 7 November 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
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
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.
UPSC NOTES @UPSC_notes_insta · 27,818 Telegram ranks this channel #18 of 71 here — alongside 70 others — read 10 September 2026
upsc mindmaps @Mindmap_upsc · 18,695 Telegram ranks this channel #21 of 72 here — alongside 71 others — read 4 October 2026
UPSC GS PYQs @Upsc_prelims_Pyq_Mcq · 27,259 Telegram ranks this channel #22 of 81 here — alongside 80 others — read 10 September 2026
Civil Services Simplified: Decoding the Enigma of UPSC by Dr. CP. Kaushik @Sci_TechUPSC · 19,480 Telegram ranks this channel #35 of 55 here — alongside 54 others — read 2 October 2026
Sudarshan Gurjar Unacademy @Sudarshan_Unacademy · 322,921 Telegram ranks this channel #43 of 69 here — alongside 68 others — read 10 August 2026
Rau's IAS Study Circle (Since 1953) @rausias1953 · 37,842 Telegram ranks this channel #45 of 74 here — alongside 73 others — read 31 August 2026
INSIGHT DELHI @INSIGHTICS · 42,243 Telegram ranks this channel #50 of 83 here — alongside 82 others — read 28 August 2026
Sumit Rewri @sumitrewri · 55,640 Telegram ranks this channel #52 of 77 here — alongside 76 others — read 24 August 2026
UPSC CSE Why @csewhy · 44,648 Telegram ranks this channel #59 of 73 here — alongside 72 others — read 29 August 2026
jayantparikshit @jayantparikshit · 22,169 Telegram ranks this channel #61 of 73 here — alongside 72 others — read 20 September 2026
PMF IAS Official @pmfias_channel · 36,251 Telegram ranks this channel #61 of 75 here — alongside 74 others — read 1 September 2026
UPSC Art and culture @upsc_art_and_culture · 27,334 Telegram ranks this channel #73 of 85 here — alongside 84 others — read 9 September 2026
School Of UPSC.com (Prelims + Mains-2027 Notes, Test, Question Bank) @school_of_upsc · 50,195 Telegram ranks this channel #77 of 83 here — alongside 82 others — read 25 August 2026
CSLIVE Group_UPSC @cslivegroup · 56,735 Telegram ranks this channel #77 of 78 here — alongside 77 others — read 23 August 2026
UPSC SUPER SIMPLIFIED @upscsupersimplified · 40,975 Telegram ranks this channel #80 of 91 here — alongside 90 others — read 29 August 2026
This channel appears in 15 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 9 November 2026 — this
entry's latest reading, not the date you are reading this.
“Environment and Ecology For UPSC [Official]” (@EnvirForUPSC), 10,180 subscribers as measured 9 November 2026. Telegram Register, tgregister.com/channel/EnvirForUPSC.
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.
![Telegram profile photo for Environment and Ecology For UPSC [Official]](https://cdn.tgregister.com/av/8a/8a9dcf5a59be3c5fe4112a5b58bf22a768a16f4177f55fad8aac03ef75b38678.jpg)