Ecommerce storefront — 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 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 7 other registered channels. This entry also sits inside a group of 8 channels linked by matching posts, directly or through other channels in the group; two members of the group may share no posts 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)
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 6 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 9 comparable posts for this entry, running 11 August 2025 to 18 September 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 8 channels, the one whose matching posts we hold earliest is @modaresantasisat. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_mutual · clone_source, 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 8 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. 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.
25 measurements spanning 98 days, net -57. 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 7,866–7,942 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 25
Measured (UTC)
Subscribers
Change
11 Nov 2026, 20:47
7,876
+1
7 Nov 2026, 13:07
7,875
-2
4 Nov 2026, 09:01
7,877
-5
1 Nov 2026, 11:37
7,882
-5
29 Oct 2026, 04:40
7,887
-2
26 Oct 2026, 05:31
7,889
+1
23 Oct 2026, 08:38
7,888
-3
20 Oct 2026, 05:11
7,891
-5
17 Oct 2026, 04:18
7,896
-1
14 Oct 2026, 12:09
7,897
-6
10 Oct 2026, 13:39
7,903
+2
4 Oct 2026, 18:56
7,901
-4
25 Sept 2026, 08:40
7,905
+2
13 Sept 2026, 13:59
7,903
-4
9 Sept 2026, 09:16
7,907
-7
4 Sept 2026, 00:35
7,914
-6
31 Aug 2026, 19:08
7,920
-3
25 Aug 2026, 17:23
7,923
-4
22 Aug 2026, 12:44
7,927
+1
19 Aug 2026, 13:26
7,926
first reading
Engagement
21 posts held, back to 11 August 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 36 pages of 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 21 posts for this entry, the most recent from 18 September 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
11m 49s
Average length
1m 41s
Measured directly from 7 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
145 reactions across 15 posts, in 11 distinct kinds. The most used accounts for 42.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
62
42.8%
👍
26
17.9%
😢
24
16.6%
👏
10
6.90%
💔
8
5.52%
😁
5
3.45%
🔥
3
2.07%
🤔
3
2.07%
😱
2
1.38%
👎
1
0.69%
😭
1
0.69%
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 17 of the 21 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 145 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 21 most recent posts we hold, published 11 August 2025 to 18 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.
#پرسش_پاسخ_قانون_کار
❓پرسش و پاسخ منتخب روز (کارگران و کارفرمایان)
آیا به محض پر شدن ۲۰ سال سابقه در مشاغل سخت و زیان آور، میتوان ترک کار کرد ؟
🔗مشاهده پاسخ لینک زیر را لمس نمایید👇
همراه ما باشید.🙏🙏
کاربان
https://whatsapp.com/channel/0029VaoSbue4IBhKyOZN9a36
ما گفتگوها را به فرصت، نوآوری را به عمل و حرکت را به نتیجه تبدیل می کنیم.
انرژی بلندتر، ترافیک بزرگتر و دید ما واضح تر از همیشه است. ما فقط شرکت نمی کنیم، بلکه رهبری می کنیم. 🚀🔥
چرخه تبرید سردخانه از ۴ مرحله اصلی تشکیل شده: کمپرسور، کندانسور، شیر انبساط و اواپراتور.
در این فرآیند، مبرد با گردش مداوم باعث انتقال گرما و ایجاد سرمای لازم برای نگهداری مواد غذایی و محصولات میشود ❄️
در این پست، به زبان ساده کل چرخه رو توضیح دادیم 👇
#سردخانه #چرخه_تبرید #تبرید_صنعتی #مهندسی_تبرید #کندانسور #اواپراتور #شیر_انبساط #کمپرسور #سیستم_سرمایش
#hvc #چیلر #تهویه_مطبوع #اواپراتور #تهویه #کولر
🌟 به کانال دانستنیهای کارگر بپیوندید! 🌟
دوستان و همکاران عزیز،
اگر به دنبال اطلاعات مفید و دانستنیهای جالب درباره کارگران و حقوق آنها هستید، کانال ما را از دست ندهید! در این کانال، مطالب آموزشی، نکات حقوقی، و اخبار مهم دنیای کارگری را با هم به اشتراک میگذاریم.
لینک کانال: https://whatsapp.com/channel/0029VaoSbue4IBhKyOZN9a36
لطفاً این لینک را با دوستان و همکاران خود به اشتراک بگذارید تا همگی از این دانستنیها…
Showing the 12 most recent of 21 posts we hold for @asplet. 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
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 1 registered channel — 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.
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 11 November 2026 — this
entry's latest reading, not the date you are reading this.
“مرکز دانش اسپلیت وکولرگازی” (@asplet), 7,876 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/asplet.
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.
