Crypto & trading — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 11 September 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 1 other registered channel. This entry also sits inside a group of 4 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 (1 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 0 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 62 comparable posts for this entry, running 26 July 2026 to 10 November 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 4 channels, the one whose matching posts we hold earliest is @GAORI777 — 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 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 4 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.
1 more channel is in this same group but not listed individually here.
Growth
50 measurements spanning 97 days, net -4,911. 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 8,124–14,509 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 50
Measured (UTC)
Subscribers
Change
11 Nov 2026, 09:19
8,861
-87
7 Nov 2026, 10:56
8,948
-77
4 Nov 2026, 17:28
9,025
-85
1 Nov 2026, 09:05
9,110
-172
29 Oct 2026, 08:46
9,282
-170
26 Oct 2026, 05:17
9,452
-184
22 Oct 2026, 21:00
9,636
-185
20 Oct 2026, 02:18
9,821
-99
17 Oct 2026, 09:07
9,920
-80
16 Oct 2026, 08:05
10,000
-71
15 Oct 2026, 09:08
10,071
-74
14 Oct 2026, 12:16
10,145
-113
13 Oct 2026, 01:20
10,258
-190
8 Oct 2026, 18:02
10,448
-171
4 Oct 2026, 09:20
10,619
-186
25 Sept 2026, 20:21
10,805
-259
19 Sept 2026, 07:37
11,064
-34
16 Sept 2026, 18:59
11,098
-152
14 Sept 2026, 18:16
11,250
-160
13 Sept 2026, 04:37
11,410
first reading
Engagement
98 posts held, back to 26 July 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 67 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
1.34%
avg views ÷ 8,861 subscribers
Avg views / post
119
23 posts measured
Reaction rate
1.35%
reactions ÷ views · ER floor
Posts in window
23
of 98 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. It is computed over the 21 of 23 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 11 November 2026
Posts held
98 (26 July 2026 – 11 November 2026)
Views total
2,735
Reactions total
36
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 12:53 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.
What this channel posts
Photos
≈8,470
Videos
≈159
Links
≈13,400
Lifetime counters from Telegram’s own channel header, read 11 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
1m 22s
Average length
27s
Measured directly from 3 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
388 reactions across 93 posts, in 3 distinct kinds. The most used accounts for 50.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
194
50.0%
🔥
104
26.8%
👍
90
23.2%
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 93 of the 98 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 388 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 98 most recent posts we hold, published 26 July 2026 to 11 November 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.
Telegram Stars
Stars received
43
across the posts below
Posts paid on
28
of 98 we hold a reading for · 29%
Most on one post
4
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @GAORI777. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 98 most recent posts we hold for this entry, published 26 July 2026 to 11 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 23 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
😀 AVEAI 5주년 이벤트, 총 상금 최대 70,000 USDT
11.10 15:00 ~ 11.30 23:59 (KST 12.1 00:59까지)
🏃♂️시작
1. ave.ai/anniversary → 'Log in / Sign up'
2. AVE 앱에서 AI Wallet 만들기 (항해 3번, 5번, 친구 초대에 필요)
🎯미션 5개
1. 현물 200 USDT 이상 거래 → 최대 20,000 USDT, 거래액 상위 300명
2. 주식 토큰 200 USDT 이상 거래 → 최대 10,000 USDT, 거래액 상위 300명
3. AI Wallet Earn 1,000 USDT 이상 가입 → 최대 5,000 USDT, 완주자 전원
4. 무기한 선물 200 USDT 이상 거래 → 최대 14,000 USDT, 거래액 상위 200명
5. 앱 Q…
📣 AVE.AI 5주년 기념 이벤트: 70,000 USDT (약 1억 원 상당) 규모의 대축제!
한국인은 웹과 app에서 한국어로 사용해주셔야 합니다 필참
Sail to the Stars (별을 향한 항해)
⏰ 이벤트 기간: 2026년 11월 10일 15:00 ~ 11월 30일 23:59 (UTC+8)
🚀 5대 항해 (미션 참여)
* 스팟(현물), 주식 및 선물 거래: 200 USDT 이상 달성
* AI 월렛 예치(Earn): 1,000 USDT 이상 달성
* 스캔 투 페이(Scan-to-Pay): 20 USDT 이상 달성
🏆 랭킹 보상 (리더보드)
* 현물 상위: 300명
* 주식 상위: 300명
* 선물 상위: 200명
✨ 5주년 스페셜 항해 보상
* 5개 항해 중 어떤 미션이든 3개 이상 완료 시, 총 10,000 …
😀 AveAI에서 Elysium 토큰 사는 법
순서만 짧게 정리해 볼게요!(BNB는 거래소 말고 Ave.ai 앱 지갑에 있어야 함)
1. 아래 가운데 버튼 → 위쪽 'Swap & Bridge' 탭
2. BNB → HYPE(HyperEVM) 크로스체인 스왑
- 보내는 쪽 BNB, 받는 쪽 HYPE(HyperEVM) 고르고 'Swap' 누르기(예시: 0.01 BNB → 0.091 HYPE, Relay 경로 약 2초, 브릿지 수수료 약 $0.08)
3. HYPE를 Elysium으로 브릿지
- 이번엔 보내는 쪽을 방금 받은 HYPE로, 받는 쪽을 HYPE(Elysium)로 바꾸고 다시 'Swap'.
4. Scan 화면 → 오른쪽 위 체인 필터 → 'Elysium' 체크 → 'Confirm'
5. 원하는 토큰 → 'Buy' 탭 → 수량(HY…
🧪 조만간 열리는 ELYSIUM 관련 밈코인을 보러 들어갔음.
돈포하님이 알려주는 거 보고 한번 쭉 보고 있는 와중에 브릿지는 뭐 버너 지갑으로 해라 뭐다 하는 이슈가 있길래 그냥 밈코인 트레이딩 터미널들 살펴봤음.
$AGENTK (0xBd453B650E84957be00E3C24fcD66E739a187804)으로 찾아봄
- AVE.AI - 제일 빨리 상장시킴 거래 가능
- FOMO, GMGN - 그냥 없음 ㅄ
- Pump.fun - 있는데 최고점에 한참 늦게 상장시킴
지금 AVE.AI에서도 돈 싸 들고 갔는데 살짝 아쉬운 건 하이퍼EVM → ELYSIUM만 브릿지 기능이 있음.
조만간 브릿지 추가해 준다 하고, 일단 뭐 피드백 넣으면 티키타카가 오는 점에서 아주 훌륭함.🍎
😀 AVE.AI 하러가기
📣AVE ELYSIUM체인 공식 지원
- DEX중에서는 가장 많은 온체인과 가장 빠르게 움직이는 AVE
- 과거 ARC체인도 발빠르게 움직여서 100배 500배까지 주식을 주었던 기억이있습니다 (과거 채널 포스팅 확인)
- 엘리시움 또한 AVE에서 거래한다면 한눈에 빠르게 거래 가능
📣ave거래하러가기: LINK
😀 AVE × Paros × PROPER 2라운드 트레이딩 대회(총 상금 약 7,100만 원)
- 총 100,000 PROS 규모의 트레이딩 대회가 진행.
- 기간: 11월 5일 18:00 ~ 11월 19일 (UTC+8)
🏆 TOP 200 랭킹전 (85,000 PROS)
☺️"Paros 체인의 TradeProsper 런치패드 토큰 거래자" 대상으로, 유효 가중 거래량 상위 200명에게 상금 지급
🎁 적격 트레이더 럭키 풀 (15,000 PROS)
☺️상위 200위 밖의 트레이더 중 누적 유효 가중 거래량 1,000 PROS 이상 달성자에게 거래량 비율에 따라 차등 지급
⚡️ 특별 부스터
☺️본딩 곡선에서 발생한 순매수 거래량에는 5배 가중치 적용
☺️상위 200위에 진입하지 못해도 최소 거래량을 충족하면 보상 대상이 될 수 있으며,…
👍 4,000만 달러 김치 트레이더의 비밀.txt 👍
밈코인으로 4,000만 달러를 벌었다는
한국인 트레이더 이야기 들어보셨나여?
솔라나에서 활동하는 김치 트레이더(@kimchi1x)인데
TRUMP 밈코인으로 약 4,000만 달러를 벌었다는
소문이 퍼지면서 엄청난 화제가 됐었는데여.
근데 재미있는 건 실제로 4,000만 달러를
벌었다는 거래 기록은 아직 검증되지 않았다는 거에여.
대신 온체인 분석 과정에서 흥미로운 거래가 발견됐는데여.
김치 트레이더와 관련된 것으로 알려진 지갑이
STAR 토큰 출시 직후 약 400달러어치를 매수하고
이후 45,000달러 이상에 매도했다는 분석이 나왔슴다.
물론 해당 지갑이 실제 본인 것인지는
확실하게 검증된 건 아니라고 하네여.
여기서 중요한 건 누가 얼마를 벌었냐보다
수익을 낸 지갑이 어떤 방식…
🔵 Ave.ai 모바일 앱 업데이트 소식
Ave.ai는 여러 체인의 밈코인을
분석하고 거래할 수 있는
글로벌 온체인 트레이딩 플랫폼입니다!
이번에 모바일 앱에
새롭게 기능들이 추가되었다고 해요.
1️⃣ 거래 및 전략 기능 개선
• 원탭 매도로 원금을 회수하고, 거래 전략을 더욱 유연하게 설정할 수 있습니다.
• 자동 매도 전략에 트레일링 익절과 트레일링 손절 기능이 추가되었습니다.
2️⃣ 차트 및 시장 데이터 개선
• 캔들 차트 하단에 ‘내 포지션’ 플로팅 바가 추가되었습니다.
• 캔들 차트 상세 페이지에서 표시할 토큰 정보를 직접 설정할 수 있습니다.
• FOMO 콜 모니터링, FOMO 마커, 토큰별 콜 이력 기능이 추가되었습니다.
3️⃣ 계정 및 사용자 경험 개선
• Google 로그인 기능이 추가…
⭐️Ave.ai 온체인 거래 핵심 용어 정리
Ave.ai에서 코인을 살펴보면 다양한 아이콘과 용어를 확인할 수 있습니다.
이 표시들의 의미만 알아도 어떤 지갑이 매수하고 있는지, 개발자가 매도 중인지, 위험 신호는 없는지 파악하는 데 도움이 됩니다.
✔️ 1. 코인 관련 용어
- Gem: 여러 지표를 분석해 선별한 주목할 만한 코인
- Potential Gems: 성장 가능성이 있는 코인 후보
- Binance Alpha: 바이낸스 알파 관련 코인 (현물 상장과는 별개)
- Rug Pull: 개발자의 대량 매도나 유동성 회수로 급락한 코인
✔️ 2. 지갑 관련 용어
- Smart Money: 과거 거래 성과 등을 기준으로 분류된 지갑
- Whale: 많은 자산을 보유한 고래 지갑
- KOL: 영향력 있는 인물과 관련된 지갑
- DEV:…
❤1
Showing the 12 most recent of 98 posts we hold for @GAORI777. 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.
Posts recorded as deleted after publishing
We recorded 1 post on @GAORI777 as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
10 November 2026
Most recent seen missing
10 November 2026
Median time before seen missing
16 hours
Seen missing in the last 30 days
1
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
1
we ourselves saw one of these resolve, at some point
Never seen alive
0
vacant every time we have ever looked
@GAORI777 named 1 handle 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.
Evidenced gone
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
@predictfikor named in 39 posts, 8 August 2026 – 3 September 2026 · confirmed gone 14 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
Appears in Telegram’s recommendations for other channels
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.
갓물주 (코인정보, 돈되는거) @godmulzoo · 22,634 Telegram ranks this channel #40 of 81 here — alongside 80 others — read 19 September 2026
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.
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.
“코인시티 x MEMECITY” (@GAORI777), 8,861 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/GAORI777.
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.