Other / unclassifiable — 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 54% 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 3 other registered channels. They sit inside a group of 5 channels that share the same post bodies with each other. 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 (6 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. None of the 0 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 26 comparable posts for this entry, running 31 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 5, the earliest publisher we hold is @ItsLetter17th. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_mutual · clone_source, last confirmed 8 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 4 other registered channels, 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.
15 measurements spanning 16 days, net -112. 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 62,293–62,456 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
22 Aug 2026, 10:09
62,321
+9
20 Aug 2026, 22:03
62,312
-19
19 Aug 2026, 20:52
62,331
-5
18 Aug 2026, 21:05
62,336
-24
17 Aug 2026, 20:04
62,360
-5
16 Aug 2026, 15:18
62,365
-32
14 Aug 2026, 23:35
62,397
-38
13 Aug 2026, 11:38
62,435
-2
12 Aug 2026, 08:05
62,437
+3
11 Aug 2026, 07:51
62,434
+2
10 Aug 2026, 08:50
62,432
+15
9 Aug 2026, 11:51
62,417
+13
8 Aug 2026, 10:56
62,404
-23
7 Aug 2026, 07:56
62,427
-6
6 Aug 2026, 10:04
62,433
first reading
Engagement
81 posts held, back to 31 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 35 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
14.3%
avg views ÷ 62,321 subscribers
Avg views / post
8,900
81 posts measured
Reaction rate
3.53%
reactions ÷ views · ER floor
Posts in window
81
of 81 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 22 August 2026
Posts held
81 (31 July 2026 – 22 August 2026)
Views total
720,771
Reactions total
25,472
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
22 Aug 2026, 13:08 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
≈1,950
Videos
≈341
Links
≈3,440
Lifetime counters from Telegram’s own channel header, read 22 August 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
16m 47s
Average length
1m 03s
Measured directly from 16 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
25,472 reactions across 81 posts, in 22 distinct kinds. The most used accounts for 40.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
10,384
40.8%
🙏
4,820
18.9%
👍
3,107
12.2%
🔥
2,394
9.40%
💯
2,081
8.17%
👏
794
3.12%
❤🔥
373
1.46%
⚡
352
1.38%
🕊
269
1.06%
✍
199
0.781%
🥰
185
0.726%
🫡
108
0.424%
🏆
102
0.4%
🎉
94
0.369%
🍾
69
0.271%
👌
60
0.236%
😇
39
0.153%
🆒
16
0.063%
😍
9
0.035%
🤝
7
0.027%
2 further kinds
10
0.039%
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 81 of the 81 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 25,472reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 81 most recent posts we hold, published 31 July 2026 to 22 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.
Telegram Stars
Stars received
216
across the posts below
Posts paid on
81
of 81 we hold a reading for · 100%
Most on one post
17
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @MrPool_Q. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 81 most recent posts we hold for this entry, published 31 July 2026 to 22 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
🔻YOUR TISSUE IS COLD.
STIFF.
LOCKED.
And nothing you put on the surface reaches it.
Heating pads warm your skin.
Hot baths warm the first few millimeters.
Creams sit on top and do nothing underneath.
The problem is not on the surface.
The problem is deep.
Locked joints. Compressed discs. Muscles that haven't fully relaxed in months. Fascia that holds tension like a fist that won't open.
You need heat that goes i…
🔻THE ROTHSCHILDS JUST LOST THE WEATHER CONTROL.
They had the sky for 47 years. Not poetically. Literally. Through a network of 22 atmospheric modification stations capable of directing hurricanes, inducing droughts, causing floods, and creating earthquakes—on demand, on schedule, to any coordinate on Earth.
It was called CLIMATE THRONE. It was funded by a web of NGOs, carbon credit exchanges and green energy foundat…
🔻 THE FDA GATE JUST GOT A NEW KEY — AND MOST PEOPLE ARE WATCHING THE WRONG DOOR.
Not with another campaign promise.
With a name.
President Trump has nominated Dr. Heidi Overton, MD, PhD, to lead the Food and Drug Administration.
If the Senate confirms her, she will inherit the agency that sits between American families and the rules governing medicines, vaccines, food safety, and drug pricing.
That is why this ap…
🔻BREAKING: FIRST-EVER STUDY LINKS VACCINES TO THE 10,000% RISE IN ALPHA-GAL SYNDROME
We found more than 90% of U.S. children are injected with ~54 mg of alpha-gal-bearing mammalian gelatin through routine childhood vaccines before school entry.
The evidence points to two possible pathways:
1) DIRECT: Vaccines may DIRECTLY promote alpha-gal sensitization.
2) PRIME-BOOST: Vaccines may PRIME the immune system, so a …
🔻YOUR BODY RUNS ON FREQUENCY.
Not on supplements.
Not on caffeine.
Not on willpower.
Frequency.
Every cell, every nerve, every joint in your body communicates through an electromagnetic signal.
When that signal is strong — you move freely, sleep deeply, recover fast, and feel like yourself.
When that signal breaks down — everything follows.
Pain spreads.
Fatigue sets in.
Inflammation builds.
Aging accelerates.
…
🔻 THE ONCOLOGIST WHO STOPPED PRESCRIBING
"I have been an oncologist for 22 years. I have prescribed chemotherapy to over 4,000 patients. Last month, I stopped. I will never prescribe it again. And I need to tell you why."
I graduated from Johns Hopkins in 2004. I believed in the system. I believed chemotherapy was the best tool we had. I watched patients suffer through it because I genuinely believed it was giving …
🔻1954.
The year they discovered it.
The year they realized what human frequency recovery could actually do.
And the year they decided you shouldn't have it.
For 70 years, the most powerful frequency technologies were locked behind closed doors.
Kept in private clinics. Used in exclusive recovery rooms by those who could afford to never be sick.
They understood that the body is an electromagnetic system.
They under…
🔻BREAKING NEWS: First in the World IVERMECTIN, Mebendazole and Fenbendazole Protocol for CANCER has been peer-reviewed & published!
The NEWS is spreading, our paper is everyplace lately! 😃
BIG PHARMA is attacking our Fenbendazole paper on 3 Stage 4 Cancer patients now Cancer Free! It will be resubmitted and published soon!
Well I have recently been attacked by Canadian authorities for my revolutionary Cancer resea…
🔻THIS IS THE FUTURE!
BIOMETRIC IDENTITY. INSTANT SETTLEMENT. ZERO FRICTION.
THIS IS THE ARCHITECTURE OF THE FUTURE FINANCIAL SYSTEM.
THE OLD MODEL RUNS ON DELAY, DEBT, AND PERMISSION.
THE NEW ONE RUNS ON SPEED, VERIFICATION, AND ALIGNMENT.
🟩 ISO 20022 IS THE LANGUAGE.
🟩 TIER 4B IS THE ACCESS POINT.
MONEY MOVES IN REAL TIME.
IDENTITY BECOMES THE KEY.
INFRASTRUCTURE REPLACES INTERMEDIARIES.
MOST WILL SEE PLASTIC.
…
🔻Four deputies from the Harris County Sheriff’s Office in Texas have d1ed by su1cide in the past six weeks.
Something very strange is going on here…
Do you think they uncovered a human trafficking operation and were silenced?
Share !
⟁
https://t.me/MrPool_Q
🔻BREAKING: SWITZERLAND BANS MAMMOGRAPHY – THE MEDICAL FRAUD UNVEILED
Switzerland has just become the first country to ban mammography, exploding the truth behind one of the biggest frauds in medical history. For decades women have been terrorized, misdiagnosed and mutilated by a system not designed to heal, but to profit. Now the mask is removed.
Mammography was never about saving lives. It was about making patient…
🔻 In 2011, a neuroscientist at MIT, Dr. Li-Huei Tsai, made a discovery that should have been on the front page of every newspaper on Earth.
She exposed mice with advanced Alzheimer’s disease to a flickering light flashing at exactly 40 Hz—forty times a second. Nothing more. No dope. No operation. Light of a particular frequency.
Within an hour the amyloid-beta plaques in their brains, the protein deposits that defi…
❤158🙏85💯30👍23🔥10🕊7⚡5✍4
Showing the 12 most recent of 81 posts we hold for @MrPool_Q. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Citation-graph rank
Citation-graph rank — 31,968 of 1,584,142entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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 48 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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.
Domains linked from posts
One domainthis channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
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 22 August 2026 — this
entry's latest reading, not the date you are reading this.
“Mr. Pool” (@MrPool_Q), 62,321 subscribers as measured 22 August 2026. Telegram Register, tgregister.com/channel/MrPool_Q.
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.