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Channel

캇즈의 크립토 노트📝☕️

@Katzenote

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

6,782subscribers

-34 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001679635363
TypeChannel
Username@Katzenote
CreatedBetween 1 December 2021 and 30 April 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live13 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/Katzenote

Growth

6,7826,8166,7996 August 2026 — 6,816 subscribers6 August 2026 — 6,816 subscribers9 August 2026 — 6,795 subscribers13 August 2026 — 6,782 subscribers6 August 202613 August 2026
4 measurements spanning 7 days, net -34. 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 6,777–6,821 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 01:266,782-13
9 Aug 2026, 19:216,795-21
6 Aug 2026, 22:046,816no change
6 Aug 2026, 11:466,816first reading

Engagement

18 posts held, back to 15 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 10 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
5.81%
avg views ÷ 6,782 subscribers
Avg views / post
394
4 posts measured
Reaction rate
0.126%
reactions ÷ views · ER floor
Posts in window
4
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. It is computed over the 2 of 4 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 28 July 2026
Posts held18 (15 June 202628 July 2026)
Views total1,575
Reactions total1
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 02:46 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

14 reactions across 5 posts, in 3 distinct kinds. The most used accounts for 50.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
custom 5235607297517953867750.0%
535.7%
🔥214.3%

Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it isTelegram’s.

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 6 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 14reactions 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 15 June 2026 to 28 July 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.

Recent posts

28 Jul 2026, 05:16 UTC278 views0 reactionsread 12 August 2026
Forwarded from @ryotmadnessPhoto

요즘은 바이브코딩 등 여러가지 일을 할때 아래에 워킹패드를 두고 걸으면서 말로 지시를 내리면서 일을 하는데, 이게 참 쓸만합니다. 이게 무슨 테크너드들이나 하는 돈ㅈㄹ 조합이라고 생각할 수 있는데, 샤오미 워킹패드는 고작 6만원 정도면 당근에서 살 수 있고, 마이크 셋업은 그냥 typeless나 meetly같은 것들 쓰면 무료라서 문제가 되는 부분이 하나도 없음. 일하면서 유산소 운동은 정말 개꿀 중의 개꿀임. 시간도 아끼고 일도 집중 잘 되네요. (참고로 아래에 코드나 잡다한 뭔가가 없는 이유는 너무 꼴보기 싫어서 gpt로 지워버렸기 때문입니다 ㅋㅋ)

25 Jul 2026, 00:01 UTC321 viewsread 12 August 2026
Forwarded from @honey_box_mainPhoto

와우 Opus5 출시 성능은 Fable 5 보다 좋으면서 가격은 쌈. Fable 왜 쓰죠?

22 Jul 2026, 06:44 UTC459 viewsread 12 August 2026
Forwarded from @wojack_capital

fable 에서 opus 무한 강등을 겪으면서 알게된 매커니즘인데 내용만 보고 바로 opus 로 바꾸지는 않음 주로 에이전트가 cli 명령어를 써야 하는 상황에서 강등이 많이 됨 그러니까 ㅈ같은걸 시켜도 지식이나 로직 등은 뽑아먹을수는 있다는 소리

18 Jul 2026, 04:21 UTC517 views1 reactionsread 12 August 2026
Forwarded from @moneybottlePhoto

Fable, 구독 모델에 영구 포함

1

12 Jul 2026, 07:47 UTC615 viewsread 12 August 2026
Forwarded from @cryptocurrencymagePhoto

녹사 곧 펌프펀 턱밑까지 도달

11 Jul 2026, 23:28 UTC596 views1 reactionsread 12 August 2026
Photo

👀에이전틱 코딩 프론티어 모델 후기: Fable 5 vs GPT-5.6-SOL 한 줄로 요약 = 가격 효율성만 따졌을 때는 GPT-5.6-SOL이 압도적으로 좋습니다. 토큰당 가격도 훨씬 저렴하고, 동일한 작업을 완수하는 데 필요한 토큰 수도 더 적은 편입니다. 다만 속도까지 빠르냐고 하면, 꼭 그렇지는 않습니다. ULTRA 모드로 사용하면 생각하는 시간이 상당히 길어져 몇 시간이 걸리기도 합니다. 기존에 2시간이면 끝날 작업이 체감상 4~6시간까지 늘어나는 경우도 있습니다. 현재까지 가장 만족스러웠던 사용 방식은 두 모델이 크로스체크 해서 서로의 단점을 보완하도록 워크플로우를 구성하는 것 Plan 모드에서 각 모델이 제시한 thesis를 서로 교차 검증하게 하고, 약 4턴 정도 주고받으면 꽤 완성도 높은 결과물이 나옵니다. 슬슬 대란

custom 52356072975179538671

11 Jul 2026, 16:50 UTC699 views7 reactionsread 12 August 2026
Photo

👀럴커가 가니 오늘 점심먹고 산게 이게 되네요 $35.61 -> $1581.1 (+4387.65%)

custom 523560729751795386761

11 Jul 2026, 16:34 UTC210 viewsread 12 August 2026
Forwarded from @Yndegen

530A(Trump Account)와 Robinhood의 관계 530A는 미국의 미성년자를 위한 장기 투자계좌로, 2025~2028년 출생한 적격 아동에게는 미국 재무부가 초기 자금 1,000달러를 지원함. 여기서 중요한 것은 Robinhood의 역할 미국 재무부는 BNY를 금융대리인으로 지정했고, Robinhood는 530A 계좌의 브로커이자 초기 수탁자 역할을 맡았음. 즉, 기존 Robinhood 일반 증권계좌를 그대로 사용하는 것은 아니지만, 530A 전용 앱과 계좌 시스템에는 Robinhood의 기술과 금융 인프라가 활용됨. 핵심은 다음과 같음. ✅ 530A 계좌는 별도의 Trump Accounts 앱을 통해 관리 ✅ Robinhood가 브로커 및 초기 수탁자 역할을 담당 ✅ 정부의 1,000달러 지원금과 추가 납입금이 장기적으로

10 Jul 2026, 13:13 UTC254 viewsread 12 August 2026
Forwarded from @JUSTCRYT

GPT-5.6 Sol 짧은 후기 써본 결론: Fable보다 좋음. 벤치마크 얘기 다 필요없고 핵심은 하나 — 삽질을 안 함. Fable은 똑똑한데 가끔 이상한 길로 새서 몇 턴 날려먹는 경우가 있었음(너프) Sol은 그냥 시킨 거 끝까지 감. 명세 주면 딴짓 안 하고 완주함. 코딩 에이전트한테 원하는 게 결국 이거 아님? 가격도 Fable 절반에 토큰도 덜 씀. 애매한 설계 논의 같은 건 Fable이 낫다는 평도 있는데, 방향은 어차피 내가 정하고 시키는 입장이라 나한텐 의미 없음. 하루 만에 메인 Sol로 갈아탐

10 Jul 2026, 08:53 UTC276 views2 reactionsread 12 August 2026
Forwarded from @moneybottlePhoto

Cursor 벤치 랭킹 1. Fable 5.0 2. Gpt 5.6 Sol 3. Grok 4.5 4. Gpt 5.6 terrra 5. Opus 4.8 6. Sonnet 5.0

🔥2

9 Jul 2026, 09:56 UTC346 viewsread 12 August 2026
Forwarded from @qtrealm

[트레이딩 프레임워크 간단 비교] CCXT 거래소 커넥터 매우 풍부 // 스윙 트레이딩 할 때는 유리할 것 같은데, 차익거래에 바로 쓰기는 조금 어렵습니다 (https://github.com/ccxt/ccxt) HummingBot 커넥터 약 풍부 // 0.5s 정도마다 의사결정을 할 수 있어서, 적당한 아비트라지 + MM에 쓰기 좋습니다. Avellaneda & Stoikov 라던가 XEMM 같은 구현체 예시가 있기도 하고, Dex 연동도 가능해서 범용적으로 쓰기도 좋고, intent만 잘 주면 에이전트가 알아서 전략 잘 짜주는 프레임워크 (다만, 1 Event Loop 내에서 모든걸 처리해야해서 복잡한 연산 있는 경우 외부에서 주입을 해줘야 하는 등 복잡해지면 신경쓸게 많아집니다.) (https://github.com/humming

Showing the 12 most recent of 18 posts we hold for @Katzenote. 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 — 887,994 of 1,350,102entries 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

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.

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 13 August 2026 — this entry's latest reading, not the date you are reading this.

“캇즈의 크립토 노트📝☕️” (@Katzenote), 6,782 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/Katzenote.

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.