Health & wellness — 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 11 August 2026 and assigned it the closest of 31 fixed categories, at 98% 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 (5 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 4 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 19 comparable posts for this entry, running 18 June 2025 to 18 April 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 @DrJBhattacharya. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_mutual, 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.
4 measurements spanning 6 days, net -12. 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 2,695–2,711 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Aug 2026, 10:48
2,697
-5
9 Aug 2026, 17:41
2,702
-7
6 Aug 2026, 11:06
2,709
no change
6 Aug 2026, 09:55
2,709
first reading
Engagement
20 posts held, back to 27 May 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 2 pagesof Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 18 April 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
16m 43s
Average length
1m 17s
Measured directly from 13 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
794 reactions across 20 posts, in 7 distinct kinds. The most used accounts for 31.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
246
31.0%
❤
219
27.6%
👏
201
25.3%
🔥
105
13.2%
😢
20
2.52%
🤮
2
0.252%
💩
1
0.126%
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 20 of the 20 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 794reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 27 May 2025 to 18 April 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.
🚨 MAJOR WIN in the fight against chronic disease 🚨
A simple, team-based care model significantly reduced high blood pressure in high-risk patients.
✔️ Health coaching ➡️ Simple solutions that work
✔️ Home BP monitoring ➡️ Lower costs for patients
✔️ Care coordination ➡️Real results in the communities that need it most
💡 Result: Big drops in blood pressure → fewer heart attacks, fewer strokes, and healthier America…
#DYK: Death rates among women stemming from heart disease are higher than those of men.
A huge part of MAHA involves helping American women live healthier lives. Meeting that challenge in the days ahead will require a renewed focus on establishing a true gold standard for women’s health research.
NIH is up to that challenge. 👩🔬
🍴Everyone knows the sensation of “eating” with our eyes and noses before food meets mouth. However, much less is known about the information superhighway, known as the vagus nerve, that sends signals in the opposite direction — from your gut straight to your brain.
An NIH-funded study from Stanford University has identified a critical link between the bacteria that live in your gut and the cognitive decline that oft…
At NIH, we’re accelerating the future of medical research, advancing innovation and repurposing existing drugs to deliver new treatments faster for the American people
Scientific journals like Lancet and Nature, which endorsed Joe Biden for president, are not trustworthy sources to comment on reforms in public health. They traded science for politics, and have not altered course since.
https://pmc.ncbi.nlm.nih.gov/articles/PMC10202798/
The Lancet published the fake Surgisphere paper and embraced the Covid origins cover up. Sec. Kennedy is fixing the mess they helped make.
Physician, heal thyself.
Is it just me, or are all the @WHO high officials and scientists who pushed the world into lockdown in 2020 now swearing up and down that they never recommended lockdown? I, for one, have no confidence that they would not recommend the world lock down again, given the chance.
Drink your whole milk 🥛 as we celebrate President Trump signing a landmark piece of legislation!
Paired with the 2025 to 2030 Dietary Guidelines, this marks a major step forward for real food and the families we serve. Whole milk delivers essential vitamins and nutrients for strong health and growing kids. A huge win for all Americans
Starting in 1973, my mom ran an at home day care. Six kids, zero to 5 yrs old, 8 to 10 hrs a day, mostly by herself, for decades. Her kids still visit her.
She never got a million dollar gov't grant for it.
States that fund fraud in the name of compassion will get fraud alone.
It’s important that we pay attention to the evidence when it comes to medicalized treatment of gender dysphoria in young people.
Based on a new report, @HHSgov experts agree that the harms outweigh any potential benefits. Watch the full discussion here:
https://youtu.be/nC9UP5yi7HY?si=8rG0PwQ08bxXeDAR
Canadian professional organizations abused their power to vilify and suppress the speech of dissident scientists and doctors during the pandemic.
Glad to see Alberta is moving to rectify the problem.
https://globalnews.ca/news/11536277/alberta-regulated-professions-neutrality-act/
👍13❤8👏4😢1
Showing the 12 most recent of 20 posts we hold for @JayBhattacharya. 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.
Handles this channel named that no longer answer
Dead references
2
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
2
vacant every time we have ever looked
@JayBhattacharya named 2 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@cdcgov named in 1 post, 8 August 2026 – 8 August 2026
@hhsgov named in 1 post, 8 August 2026 – 8 August 2026
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 12 August 2026 — this
entry's latest reading, not the date you are reading this.
“Jay Bhattacharya” (@JayBhattacharya), 2,697 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/JayBhattacharya.
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.