Channel
@medical_amboss
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · Posts · Citations · Telegram's recommendations · Cite this entry
1,465subscribers
+5 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1001728614715 |
|---|---|
| Type | Channel |
| Username | @medical_amboss |
| Created | Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 19 September 2026 |
| Measurements held | 14 |
| Confirmed unchanged | 1 time, most recently 19 September 2026 |
| On Telegram | t.me/medical_amboss |
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 11 August 2026 and assigned it the closest of 31 fixed categories, at 93% 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.
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.
Posts published here appear word for word on 4 other registered channels. 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.
| Posted first | Then | Overlap | Gap |
|---|---|---|---|
| @medicalcour/64912 Aug 2026, 20:24 UTC | @medical_amboss/5567 · this entry2 Aug 2026, 20:24 UTC | 1.00 | under a minute |
| @medicalcour/64955 Aug 2026, 19:00 UTC | @medical_amboss/5571 · this entry5 Aug 2026, 19:00 UTC | 1.00 | under a minute |
| @medical_amboss/5572 · this entry5 Aug 2026, 19:21 UTC | @medicalcour/64965 Aug 2026, 19:21 UTC | 1.00 | under a minute |
| @medicalcour/64975 Aug 2026, 19:59 UTC | @medical_amboss/5573 · this entry5 Aug 2026, 19:59 UTC | 1.00 | under a minute |
| @medical_amboss/5576 · this entry5 Aug 2026, 20:33 UTC | @medicalcour/65005 Aug 2026, 20:33 UTC | 1.00 | under a minute |
| @medicalcour/65035 Aug 2026, 21:32 UTC | @medical_amboss/5579 · this entry5 Aug 2026, 21:32 UTC | 1.00 | under a minute |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @medicalcour | 17 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | @medicalcour (17–0) |
| @medicalebo | 17 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | @medicalebo (17–0) |
| @medicalaccount1 | 17 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | @medicalaccount1 (17–0) |
| @medicalaccount0 | 17 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | this entry (14–3) |
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. 10 of the 45 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 20 comparable posts for this entry, running 2 August 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.
Across the whole group of 5, the earliest publisher we hold is @medicalaccount1. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_copy · clone_source, 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.
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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 19 Sept 2026, 05:56 | 1,465 | -1 |
| 14 Sept 2026, 13:36 | 1,466 | -2 |
| 10 Sept 2026, 18:35 | 1,468 | +1 |
| 5 Sept 2026, 22:39 | 1,467 | +7 |
| 2 Sept 2026, 01:28 | 1,460 | +1 |
| 30 Aug 2026, 04:57 | 1,459 | -1 |
| 26 Aug 2026, 20:54 | 1,460 | -1 |
| 24 Aug 2026, 03:53 | 1,461 | -2 |
| 20 Aug 2026, 02:25 | 1,463 | -2 |
| 17 Aug 2026, 12:44 | 1,465 | -1 |
| 13 Aug 2026, 17:46 | 1,466 | +4 |
| 10 Aug 2026, 09:30 | 1,462 | +2 |
| 7 Aug 2026, 22:01 | 1,460 | no change |
| 7 Aug 2026, 16:08 | 1,460 | first reading |
20 posts held, back to 2 August 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 1 page 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 20 posts for this entry, the most recent from 7 August 2026. An engagement rate over an empty window would be a number about nothing.
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Showing the 12 most recent of 20 posts we hold for @medical_amboss. 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.
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.
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.
This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 19 September 2026 — this entry's latest reading, not the date you are reading this.
“Medicalamboss.com shope” (@medical_amboss), 1,465 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/medical_amboss.
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.