国服国际服台服_模拟执行解密++
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Channel
@SnowKernelPD
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
27,920subscribers
+1,004 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1003764961448 |
|---|---|
| Type | Channel |
| Username | @SnowKernelPD |
| Created | Between 1 February 2026 and 20 April 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 29 September 2026 |
| Measurements held | 34 |
| Confirmed unchanged | 1 time, most recently 29 September 2026 |
| On Telegram | t.me/SnowKernelPD |
Hacking & security — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 81% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 29 Sept 2026, 23:17 | 27,920 | +258 |
| 18 Sept 2026, 01:58 | 27,662 | +146 |
| 15 Sept 2026, 23:40 | 27,516 | +53 |
| 14 Sept 2026, 04:17 | 27,463 | +89 |
| 12 Sept 2026, 15:19 | 27,374 | +105 |
| 10 Sept 2026, 11:39 | 27,269 | +26 |
| 7 Sept 2026, 04:18 | 27,243 | +79 |
| 4 Sept 2026, 10:58 | 27,164 | +14 |
| 3 Sept 2026, 00:57 | 27,150 | +19 |
| 1 Sept 2026, 22:25 | 27,131 | +11 |
| 31 Aug 2026, 18:47 | 27,120 | +17 |
| 30 Aug 2026, 18:47 | 27,103 | +25 |
| 29 Aug 2026, 19:28 | 27,078 | +18 |
| 28 Aug 2026, 17:53 | 27,060 | -7 |
| 27 Aug 2026, 21:13 | 27,067 | +29 |
| 26 Aug 2026, 23:07 | 27,038 | +5 |
| 26 Aug 2026, 01:32 | 27,033 | +15 |
| 25 Aug 2026, 01:33 | 27,018 | +16 |
| 23 Aug 2026, 15:58 | 27,002 | +29 |
| 22 Aug 2026, 03:08 | 26,973 | first reading |
70 posts held, back to 20 April 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 71 pages of Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 28 September 2026 |
|---|---|
| Posts held | 70 (20 April 2026 – 28 September 2026) |
| Views total | 290,440 |
| Reactions total | 1,078 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 30 Sept 2026, 12:38 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.
Lifetime counters from Telegram’s own channel header, read 30 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Measured directly from 1 video 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.
9,495 reactions across 69 posts, in 34 distinct kinds. The most used accounts for 24.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 2,323 | 24.5% | |
| ❤ | 2,217 | 23.3% | |
| 👎 | 1,200 | 12.6% | |
| 💩 | 672 | 7.08% | |
| 😱 | 641 | 6.75% | |
| 😭 | 473 | 4.98% | |
| 👏 | 451 | 4.75% | |
| 🤣 | 243 | 2.56% | |
| 🖕 | 179 | 1.89% | |
| 🤪 | 177 | 1.86% | |
| 🤔 | 126 | 1.33% | |
| 🤬 | 122 | 1.28% | |
| 🥰 | 117 | 1.23% | |
| 🍌 | 97 | 1.02% | |
| 🤡 | 56 | 0.59% | |
| 🤯 | 45 | 0.474% | |
| 🌭 | 36 | 0.379% | |
| 🤩 | 34 | 0.358% | |
| 🕊 | 32 | 0.337% | |
| 🤮 | 31 | 0.326% | |
| 14 further kinds | 223 | 2.35% |
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 69 of the 70 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 9,495 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 70 most recent posts we hold, published 20 April 2026 to 28 September 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.
国服国际服台服_模拟执行解密++
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1.三角洲行动国服 (DFM: China) 2.三角洲行动国际 (DFM: Global) 3.三角洲行动台湾 (DFM: Taiwan) 4.使命召唤国服 (CODM: China) 5.使命召唤国际 (CODM: Global) 6.使命召唤台湾 (CODM: Taiwan) 7.穿越火线国服 (CFM: China) 8.穿越火线国际 (CFM: Global) 9.迷你世界官服 (MiniPVE: China) 10.王者荣耀国服 (SGAME: China) 11.王者荣耀国际 (SGAME: Global) Time:03:09, September 29, 2026 驱动频道 @ZeroPD
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1.三角洲行动国服 (DFM: China) 2.三角洲行动国际 (DFM: Global) 3.三角洲行动台湾 (DFM: Taiwan) 4.使命召唤国服 (CODM: China) 5.使命召唤国际 (CODM: Global) 6.使命召唤台湾 (CODM: Taiwan) 7.穿越火线国服 (CFM: China) 8.穿越火线国际 (CFM: Global) 9.迷你世界官服 (MiniPVE: China) 10.王者荣耀国服 (SGAME: China) 11.王者荣耀国际 (SGAME: Global) LOG:CFM修复卡顿问题 LOG:三角洲修复AZ3_长弓 LOG:三角洲修复数据延迟问题 LOG:迷你世界枪战新增重力浮空 Time:16:30, September 28, 2026 驱动频道 @ZeroPD
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Video, posted without a caption
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1.三角洲行动国服 (DFM: China) 2.三角洲行动国际 (DFM: Global) 3.三角洲行动台湾 (DFM: Taiwan) 4.使命召唤国服 (CODM: China) 5.使命召唤国际 (CODM: Global) 6.使命召唤台湾 (CODM: Taiwan) 7.穿越火线国服 (CFM: China) 8.穿越火线国际 (CFM: Global) 9.迷你世界官服 (MiniPVE: China) 10.王者荣耀国服 (SGAME: China) LOG:CFM修复无效果等问题 Time:19:07, September 27, 2026 驱动频道 @ZeroPD
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1.三角洲行动国服 (DFM: China) 2.三角洲行动国际 (DFM: Global) 3.三角洲行动台湾 (DFM: Taiwan) 4.使命召唤国服 (CODM: China) 5.使命召唤国际 (CODM: Global) 6.使命召唤台湾 (CODM: Taiwan) 7.穿越火线国服 (CFM: China) 8.穿越火线国际 (CFM: Global) 9.迷你世界官服 (MiniPVE: China) 10.王者荣耀国服 (SGAME: China) Time:16:07, September 27, 2026 驱动频道 @ZeroPD
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奶龙王😡
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1.使命召唤国服 (CODM: China) 2.使命召唤国际 (CODM: Global) 3.使命召唤台湾 (CODM: Taiwan) 4.穿越火线国服 (CFM: China) 5.穿越火线国际 (CFM: Global) 6.迷你世界官服 (MiniPVE: China) 7.王者荣耀国服 (SGAME: China) Time:03:15, September 25, 2026 驱动频道 @ZeroPD
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CharacterModels.bin 模型文件 放在在/data/adb/Models
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遁地的重启游戏后,琳琅天上初始化数据后点解密就好了,然后我明天看看怎么个事
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适配范围: 三角洲国服_台服_国际 LOG:贫空想象修复解密 LOG:奶龙模式下新增血量射线 绘制内容可以下滑找到人物填充 绘制调节可以下滑找到核心切换 本地模型 在主频道置顶执行BlackSnowResources.sh Time:2:18 on September 20, 2026 驱动频道 @ZeroPD
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适配范围: 三角洲国服_台服_国际 LOG:彻底去除对纯C的支持 LOG:三角洲国服支持最新解密 绘制内容可以下滑找到人物填充 绘制调节可以下滑找到核心切换 本地模型 在主频道置顶执行BlackSnowResources.sh Time:21:01 on September 17, 2026 驱动频道 @ZeroPD
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Showing the 12 most recent of 70 posts we hold for @SnowKernelPD. 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.
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.
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 29 September 2026 — this entry's latest reading, not the date you are reading this.
“小雪频道” (@SnowKernelPD), 27,920 subscribers as measured 29 September 2026. Telegram Register, tgregister.com/channel/SnowKernelPD.
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.