Crypto & trading — 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 10 August 2026 and assigned it the closest of 31 fixed categories, at 99% 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.
Content that also appears on other registered channels
Posts published here appear word for word on 1 other registered channel. 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)
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 10 comparable posts for this entry, running 4 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.
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).
Across the whole group of 2, the earliest publisher we hold is @oracleblockchain1 — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key 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.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 1 other registered channel, 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.
9 measurements spanning 7 days, net -113. 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 25,534–25,681 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
14 Aug 2026, 16:13
25,551
-29
13 Aug 2026, 05:54
25,580
-8
12 Aug 2026, 07:14
25,588
-24
11 Aug 2026, 04:05
25,612
-16
10 Aug 2026, 04:23
25,628
-17
9 Aug 2026, 05:03
25,645
-11
8 Aug 2026, 08:16
25,656
-8
7 Aug 2026, 19:15
25,664
no change
7 Aug 2026, 19:07
25,664
first reading
Engagement
32 posts held, back to 4 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 18 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
13.4%
avg views ÷ 25,551 subscribers
Avg views / post
3,410
32 posts measured
Reaction rate
2.24%
reactions ÷ views · ER floor
Posts in window
32
of 32 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 14 August 2026
Posts held
32 (4 August 2026 – 14 August 2026)
Views total
109,241
Reactions total
2,444
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
14 Aug 2026, 15:57 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
2,444 reactions across 32 posts, in 8 distinct kinds. The most used accounts for 28.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
custom 5253519763568632249
688
28.2%
custom 5251232169497500477
396
16.2%
custom 5251622745233465229
330
13.5%
custom 5253943663955842322
309
12.6%
custom 5253965027123177591
285
11.7%
custom 5253730113886920665
187
7.65%
custom 5251234067873044837
164
6.71%
custom 5253955814418326844
85
3.48%
Custom emoji. Every 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 counts beside them areTelegram’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 32 of the 32 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 2,444reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 32 most recent posts we hold, published 4 August 2026 to 14 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.
📉 We have a scenario cancellation for $BEAT!
I decided not to take the risk and enter, as the price failed to hold at the level for even one candle.
📊 All EMAs were broken, and the price plunged downward through volume voids.
In the near future, I will review the scenario and, if possible, enter a short position.
📉 $ADA did not receive confirmation to enter the position.
Despite the initial bullish signal, the price continued to move in the opposite direction, reaching the scenario cancellation boundary.
💎 If anything changes, I will definitely let you know!
📉 $XLM continues to fall!
If the asset does not break any EMA, and shows at least one retest, we can confidently enter a short position.
Volumes continue to fall and do not suggest further growth.
📊 Trade data
Market entry: $0.168
Stop-loss: $0.194
Leverage: up to 5x
Target: $0.117
Risk: 1%
My position size: $55,000
Three things to check in the order book and metrics before entering an altcoin.
⚡️ First.
Open interest is rising, but the price is stagnant. Traders are opening leveraged positions, but no one is pushing the price anywhere. Someone is accumulating volume without moving the chart. A flat price combined with rising OI almost always discharges in one sharp move. Check OI on the exchange with the highest volume for th…
The chart shows the past, the order book shows intent, but the tape — the fact!
🤑 Today I will tell you about three things visible in the order book before the candle is drawn.
• Fake Wall.
A large order standing 3-4 ticks away from the current price and looking impenetrable. The price approaches, the order disappears. It was never intended to be executed. It was placed so you would see resistance and close early.…
📈 $XMR shows a strong bullish signal!
Entry into the position only upon confirmation!
The entry signals in this setup are:
1) Retest of EMA21/50/100
2) Breakout and retest/holding of the 0.236 Fibonacci level ($400).
📊 Trade Data
Entry order: $373-400
Stop-loss: $336
Leverage: up to 7x
Target: $475
Risk: 1%
My position size: $30 000
📈 $HYPE is exiting the bullish trend, showing bearish sentiment!
The last thing holding the price from further decline is the dynamic support in the form of EMA100 and the 0.5 Fibonacci level, a breakout of which signals a deep correction of the asset.
📊 Trade data
Market entry: $55
Stop-loss: $65
Leverage: up to 4x
Target: $34
Risk: 1%
My position size: $45,000
⚡️ You opened a position and immediately went negative. Why?
— Entry fee.
Let's calculate. Deposit $1,000, leverage 10x, position $10,000.
Taker fee on entry: $5. Fee on exit: another $5. Spread you crossed with a market order: $1. Slippage on execution: $2. Funding if you hold the position for a day: $3.
Total $16 for one trade. That's 1.6% of the deposit burned before the market made a single move.
📉 Now multi…
📉 $ZEC has been consolidating for a long time within an uptrend.
On the daily timeframe, the EMAs are giving a bullish signal; holding at the 0.618 level will be the primary signal to enter a long position.
📊 Trade details
Market entry: $500
Stop-loss: $381
Leverage: up to 3x
Target: $761
Risk: 1%
My position size: $55,000
🏆 Continuing work with $PUMP!
The asset demonstrates confident growth and a strong bullish signal of intersecting EMAs on the daily timeframe.
I consider the scenario medium-term, recommended leverage: 3x.
📊 Trade data
Market entry: $0.001615
Stop-loss: $0.001515
Leverage: up to 3x
Target: $0.001845
Risk: 1%
My position size: $40 000
⚡️ Strategy is selling bitcoin for the fourth week in a row!
From August 3 to 9, Michael Saylor’s company sold 1,690 BTC for $108.6 million at an average price of $64,262. The average purchase price of the entire reserve sits at $75,385.
That means they’re selling BELOW their own cost basis.
🪙 Every last cent went toward buying back 1,152,020 shares of STRC. This is the third buyback under the $1 billion program. …
Showing the 12 most recent of 32 posts we hold for @oracleblockchain1. 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.
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.
“Oracle Blockchain” (@oracleblockchain1), 25,551 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/oracleblockchain1.
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.
