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 11 August 2026 and assigned it the closest of 31 fixed categories, at 79% 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.
Views per post sit far above this size band
3,970 average views per post against 1,745 subscribers — an engagement rate of 227.7%. Across the 370 registered channels in the same cohort — 1,007–3,130 subscribers, posting mainly in Korean — the middle half sit between 9.10% and 35.8%, with a median of 18.8%.
What this was computed from
Window
30 days (16 July 2026 – 15 August 2026)
Posts measured
9 of 9 published in the window (3 exact, 6 rounded by Telegram)
Views totalled
35,754
Mature posts only
227.7% over 9 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal.A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_high, last confirmed 15 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.
Growth
5 measurements spanning 7 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 1,742–1,745 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
14 Aug 2026, 09:55
1,745
+1
11 Aug 2026, 03:37
1,744
+1
8 Aug 2026, 04:23
1,743
+1
7 Aug 2026, 21:01
1,742
no change
7 Aug 2026, 18:14
1,742
first reading
Engagement
18 posts held, back to 29 June 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 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
227.7%
avg views ÷ 1,745 subscribers
Avg views / post
3,970
9 posts measured
Reaction rate
0.364%
reactions ÷ views · ER floor
Posts in window
9
of 18 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 6 August 2026
Posts held
18 (29 June 2026 – 6 August 2026)
Views total
35,754
Reactions total
130
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 21:01 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.
Reaction mix
285 reactions across 18 posts, in 8 distinct kinds. The most used accounts for 38.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
110
38.6%
👍
84
29.5%
🖕
37
13.0%
👏
32
11.2%
🔥
14
4.91%
👎
4
1.40%
💯
2
0.702%
🤬
2
0.702%
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 18 of the 18 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 285reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 29 June 2026 to 6 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.
안녕하세요 앱클론 ir팀입니다.
신한투자증권 엄민용 위원의 세번 째 엄니버스, 앱클론 리포트 공유드립니다.
"헨리우스와 개발 중인 HER2+(양성) 위암 1차 치료제 후보물질 AC101은
임상 2상 mPFS가 39개월을 넘어섰고, 사망 또는 질병 진행 위험이 기존
치료제 대비 -80% (HR 0.2)라는 엄청난 데이터 확보. 2028년 상업화 대기
중이라 하반기부터 큰 성장 가능. 목표주가 설정도 가능한 바이오텍"
링크에서 원문 확인 부탁드립니다.
감사합니다.
https://www.abclon.com/board/bbs/board.php?bo_table=news&wr_id=254
존경하는 앱클론 주주 여러분, 대표이사 이종서입니다.
최근 국내외 거시 경제의 불안정과 제약·바이오 섹터 전반에 불어닥친 극심한 투자 심리 위축으로 인해, 당사의 주가 역시 큰 폭의 하락을 겪고 있습니다. 회사의 본질적 가치와 무관하게 연일 이어지는 주가 하락으로 인해 주주 여러분께서 겪고 계실 고통과 상실감에 대해 대표이사로서 무거운 책임감과 깊은 위로의 말씀을 올립니다.
다시 한번 분명히 말씀드립니다. 현재의 주가 하락은 당사 내부의 악재나 파이프라인의 펀더멘털 훼손과는 전혀 무관한 외부 수급 현상입니다. 회사의 심장인 연구개발과 사업화 시계는 그 어느 때보다 빠르고 강력하게 돌아가고 있습니다.
이를 증명하듯, 저…
https://www.abclon.com/board/bbs/board.php?bo_table=ir&wr_id=66
안녕하세요, 앱클론 IR팀입니다.
당사의 핵심 파이프라인 개발 현황 및 중장기 비전을 담은 2026년 최신 종합 IR Book 자료를 공유해 드립니다.
이번 개정판은 최근 성공적으로 마무리된 주요 파이프라인의 임상 마일스톤과 글로벌 지식재산권(IP) 확보 성과를 충실히 반영하여, 투자자 및 주주 여러분께서 당사의 기업가치를 보다 쉽고 정확하게 이해하실 수 있도록 리뉴얼하였습니다.
감사합니다.
안녕하십니까 앱클론 ir팀입니다.
스페인 마드리드에서 개최되는 ESMO(유럽종양학회) 2026이 100일 안으로 다가왔습니다. 당사의 핵심자산 AC101(HLX22)의 유방암 2상 데이터가 첫 공개될 예정(헨리우스 2026 사업보고서 기재 ESMO/ESMO ASIA)입니다.
많은 관심과 응원 부탁드립니다.
감사합니다.
안녕하세요 앱클론 IPR팀입니다.
'CAR-T 종가'로 불리는 미국 펜실베이니아 대학교(UPenn)와 공동개발한 차세대 'CD30 CAR-T' 기술의 미국 특허청(USPTO) 최종 등록 소식을 전해드립니다.
세계 최고 권위 기관과 '공동 특허권자' 등재 세계 최초의 CAR-T 치료제 '킴리아'를 탄생시킨 美 유펜과 공동 연구를 거쳐 '공동 특허권자'로 이름을 올렸습니다. 이는 당사 기술의 완성도와 대외적 신뢰도가 인정받은 결과입니다.
기존 치료제 내성 극복 (신규 에피토프 발굴) 악성 림프종 암세포 표면의 'CD30' 단백질을 타깃하되, 기존 치료제와는 전혀 다른 새로운 결합 부위(에피토프)를 공략합니다. 이를 통해 기존 치료에 불응하거나 내성이 생긴 환자들에게 대안을 제시할 수 있습니다.
기술이전(L/O) 논의 가속화 가장 까다로운 …
👍17❤5🖕4
Showing the 12 most recent of 18 posts we hold for @abclonipr. 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 — 426,046 of 1,480,688entries 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
Names
Channels on the register whose handles appear in this channel's posts.
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 14 August 2026 — this
entry's latest reading, not the date you are reading this.
“앱클론 IPR” (@abclonipr), 1,745 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/abclonipr.
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.
