Religion — 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 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 2 other registered channels. They sit inside a group of 4 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 (4 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 3 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 18 comparable posts for this entry, running 20 February 2026 to 8 July 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 4, the earliest publisher we hold is @tebmohammad — which is this entry. 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 3 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.
3 measurements spanning 4 days, net -3. 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 2,411–2,414 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
10 Aug 2026, 15:12
2,411
-3
7 Aug 2026, 09:03
2,414
no change
6 Aug 2026, 18:33
2,414
first reading
Engagement
20 posts held, back to 20 February 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 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 8 July 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
12m 51s
Average length
2m 09s
Measured directly from 6 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.
👁 آیا چشم زخم واقعیت دارد؟؟؟
⭕️ #چشم_زخم بر فرض آنکه وجود داشته باشد، قابل رؤیت با چشم نیست و از آن جایی که ما مسلمانها قائل به علم معصومین علیهم السّلام و اتصالش به علم خداوند هستیم، باید ببینیم در احادیث و روایات اسلامی در مورد چشمزخم چه دیدگاهی وجود دارد.
☘ امام صادق (علیه السلام ) میفرمایند: «اگر قبرها برای شما گشوده شوند همانا خواهید دید که اکثر مردگانِ شما با چشمزخم مردهاند، زیرا چشم زخم حقیقت دارد»
💠…
✅جهت پیدا کردن کار
🍀هر کس بیکار بماند و شغلی نداشته باشد
بعد از استحمام وپوشیدن لباس پاکیزه ، وضو بگیرد ، رو به قبله بنشیند و سوره ( یوسف) علیه السلام را بنویسد و هنگام شب از خانه خارج گشته و انرا (سوره یوسف) در شکاف دیواری پنهان کند و موقع برگشتن پشت سر خودرا نگاه نکند ، چند روز بعد او را برای شغلی دعوت میکنند و مشغول به کار می گردد🍀
بايست چند مورد حتماٌ رعايت شود:
در نوشتن آيات طهارت و وضو داشتن رعايت گردد …
✔️بهترین پزشکان جهان :
🍁 نور خورشید
🍁 آب خوردن
🍁 خواب
🍁 هوای آزاد
🍁 پیاده روی
🍁 غذای سالم
🍁 آرامش
https://telegram.me/joinchat/C38dMz_eTAISAzFnI-Nnqw. 👨👩👧👦خانواده سالم👨👩👧👦
⭕️افزايش #احتمال_دوقلوزايى :
🔹داشتن سابقه خانوادگی دوقلوزايى
🔹 چاقی وبلند بودن قد
🔹 باردارى در سن بالاى35
🔹 رژیمهاى خاص غذايى
🔹روشهای کمک باروری
🔹افزایش دفعات #بارداری
┄━═✿🍃🍃✿═━┄
✨🍏طب محمد و آل محمد(ص)✨
@tebmohammad
🔴📡من یک زنبوردار ایرانیام که کنار همسرم و پدرم در دامنههای سبلان، عسل ناب و ارگانیک تهیه میکنیم 🐝⛰
اگه تابستون اومدی اردبیل، حتماً بیا گردنهی حیران از کندوهامون دیدن کن 😍🌿
چرا عسل ما اینقدر خاصه؟
⭕️۱۰۰٪ طبیعی و خام – همونطور که زنبورها ساختن
⭕️ ارگانیک، سالم، بدون سم و آلودگی
⭕️ قابل مصرف برای دیابتیها (با مشورت پزشک)
⭕️ طعم و عطری کمنظیر از دل کوهستان
فقط یک قاشقش کافیه تا عاشقش بشی! ✨
ارائه برگه آزمایش🖥 …
#خواص گردو
خوردن پوسته های خشک داخل گردو کمک فراوانی به کاهش قند خون در افراد مبتلا به دیابت و افرادی که در
مرز ابتلا به دیابت قرار دارند می کند.این پوسته ها را آسیاب کرده و مصرف کنید.
┄━═✿🍃🍃✿═━┄
✨🍏طب محمد و آل محمد(ص)✨
@tebmohammad
💣بمب لاغری سال 2026 رونمایی شد💣
هرچی دوست داری بخور و لاغر شو
🧭رسیدن به وزن دلخواه بدون ورزش و رژیم
🧭۷ الی ۱۰ کیلو کاهش وزن تنها در یکماه
🧭دارای تاییدیه وزارت بهداشت
برای دریافت اطلاعات بیشتر و بهره مندی از تخفیف استثنایی ، همین حالا روی لینک زیر کلیک کنید.📲
https://landing.creditsw.ir/UJBQu
https://landing.creditsw.ir/UJBQu
🍃 پنـیر و خـربـزه
⚜پیامبر اکرم(ص)⚜
✍🏻هر زن بارداری که خربزه و پـنیر راباهم بخورد فرزندش خوش اخلاق و زیبا می شود
📚 بحارالانوار ۲۹۹/۶
┄━═✿🍃🍃✿═━┄
✨🍏طب محمد و آل محمد(ص)✨
@tebmohammad
تغییر قیافه خواننده معروف..سوژه ی فضای مجازی شد‼️
منم باورم نمیشد تا کامل ویدیو رو دیدم 👀
رویش مو حتی در نواحی طاس 👌🏻
3 برابر شدن حجم موها بدون روشهای تهاجمی💚
تا عید خیلی نمونده پس اگه دنبال یه تغییر خفنی همین الان شروع کن .
بزن رو لینک زیر و از تخفیف عیدانه بهره مند شو👇👇
https://landing.creditsw.ir/7646h
https://landing.creditsw.ir/7646h
#خواص کشمش
ناشتا 1 مشت کشمش بخورید تا معجزه کنه براتون
▫️منبع خوب فیبر برای لاغری
▫️دشمن سرطان
▫️کاهش استرس و تقویت اعصاب
▫️خوشبو کننده دهان
▫️رفع گرفتگی عضلات
▫️درمان یبوست
┄━═✿🍃🍃✿═━┄
✨🍏طب محمد و آل محمد(ص)✨
@tebmohammad
Showing the 12 most recent of 20 posts we hold for @tebmohammad. 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.
Citation-graph rank
Citation-graph rank — 1,074,896 of 1,151,006entries 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
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
Named by 2 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.
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.
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
@tebmohammad 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.
@darman_doa named in 1 post, 8 August 2026 – 8 August 2026
@nazrmahdavi14 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 10 August 2026 — this
entry's latest reading, not the date you are reading this.
“طب محمد و آل محمد(ص)” (@tebmohammad), 2,411 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/tebmohammad.
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.