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@laobaishare · X · Global · OTHER
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Real X profile and recent post evidence are attached for @laobaishare; some items are still pending moderation.
Risk reading
High uncertainty
Evidence
Medium · 40
Risk reading
High uncertainty
Evidence
Medium · 40
The record has unresolved uncertainty from risk tags, moderation, mixed signals, or thin context. Treat this as a review prompt.
Nothing on this page is an identity, safety, or transaction verdict — it is collected evidence plus interpretation.
Main basis
Reading limits
Image inventory
Low image inventory
14
Saved media
Image inventory
Low image inventory
14
Saved media
Only a few post images saved — sensitive / age-restricted media may be missing. Too small a sample for consistency analysis.
Post images
5
Unique images
5
Linked posts
5
Freshness
Recent
Latest captured media: 2026-10-22 00:53
Refresh only adds new media. Saved media stays archived even after the creator deletes the originals.
Quick read
Key account facts
Open
Quick read
Key account facts
Registration history
5y 5m
Follower / following
214.2K / 461
Posting evidence
30 collected
Profile density
Checkable profile evidence
Community calibration
Does this score match what you see? Your signal helps calibrate the account.
Radar score
88
Risk
low
Followers
214.2K
Following
461
Posts tracked
30
Data status
Evidence available
A real collected snapshot backs this page (updated today). Reviews and moderation may still revise this reading.
Result source: Saved + collected evidence
Saved server record plus real collected X evidence.
Latest collection run: Collected
Status: collected 30 recent post(s).
Started at 2026-10-22 00:53 · Finished at 2026-10-22 00:53
📖 Member preview
Preview
Full media inventory
Preview count only; full archive opens after member access
Linked posts
Members can inspect which posts support saved media
Interaction structure
Members see more context behind score movement, not just the score
Risk reasons
Members can read why the page asks for caution or review
History changes
Members can inspect selected historical archive and timeline context
Context only — not identity or safety conclusions.
Free: one full view per account. Member: full score logic + more reviews. Pro: deep archive + corrections.
Collected X evidence
Profile snapshot
Collected profileFollowers
214K
Following
461
Tweets
13K
Recorded at
2026-10-22 00:53
Collected media evidence
Library note
Previewing first 12 of 14. Open the archive tab for the full media library.
Banner
X media ↗Post image
Source tweet ↗Post image
Source tweet ↗Video thumb
Source tweet ↗Video thumb
Source tweet ↗Video thumb
Source tweet ↗Video thumb
Source tweet ↗Video thumb
Source tweet ↗Post image
Source tweet ↗Post image
Source tweet ↗Video thumb
Source tweet ↗Followers
214K
Following
461
Tweets
13K
Source
third_party_api

老白(每日 AI 干货✊)
Collected at: 2026-10-22 00:53
分享 AI 高价值干货:效率工具 💨 | 自托管 ⚙️ | 副业思路 💰 | 让AI成为你的超级助手,而不是焦虑来源 💪
Recent collected posts
何同学这么牛逼了?
RT @0xluffy_eth: OpenAI 官方刚发了个 Skill, 能速查网站是否中了那个 PHP 漏洞。 如果你只这个情况,建议马上用 ⬇️: 1. 你的站是WordPress / Drupal / Joomla 或其他PHP CMS,尤其是用mod_php的。…
我:“刚刚 PHP 爆了 2 个超大漏洞,涉及到全世界 70% 的网站安全 ” 我媳妇:“哪个网站 ?”
RT @punk2898: 一个冷知识:重庆在黄奇帆在任的时候房价按照“套内”面积计算,其他城市都是建筑面积,也就是算上了公摊 然而在他刚刚离任后就“魔改”成了“建筑面积”。他在任的时候 GDP 翻倍,但是房价只上涨 12%,他离任后房价开始暴涨 这是真的干实事的,但是退休…
今天互联网上最危险的东西出现了 有人做了一个 AI,能像 GPT 读英文那样读 K 线图,而且 100% 免费放出来了 它能接进 TradingView 配置,配上 opus 5.5, AI 交易系统会读每一根 K 线,在行情走出来之前就预测下一步(而且挺准) 先搞懂 KRONOS 是怎么运作的: > ChatGPT、Claude 这类大模型把词变成 token,预测下一个词 > Kronos 把每根 K 线变成 token,预测下一根 K 线 > 它预训练用了 120 亿根 K 线 下面是怎么免费把整套系统搭起来: 1. 打开 Claude Code,用 Sonnet 5.5,让它克隆 Kronos 仓库并装好环境,安装它全帮你搞定 2. 切到 opus 5.5,给它指令从 Hugging Face 加载 Kronos-small,普通笔记本就能跑(我用的是 MAC M5 pro) 3. 它会从币安免费的公共 API 拉取和你在 TradingView 上看到的同样的 K 线,任何币、任何周期,开盘、最高、最低、成交量全都有,不用注册账号 4. 让 Opus 5.5 把最近 512 根 K 线喂给 Kronos,预测接下来 24 根,就跟让大模型续写一句话一样 5. 把 sample_count 设成 100,Kronos 就会画出 100 种可能的未来,而不是只猜一个,这些路径之间的分散程度就反映了下一步的真实风险 6. 让 Opus 从这些未来路径里判断市场状态,大多数路径指向同一方向就是趋势行情,路径四散两边都有就是震荡 7. 让 Opus 把预测和市场状态转成明确的进场、出场、止损规则,再用一年历史数据回测,算上真实手续费和滑点 8. 然后用 TradingView 免费的 Lightweight Charts 库,把 Kronos 预测的路径和真实 K 线画在一起,盯几天再决定信不信它 9. 先模拟盘跑,再让 Opus 接个 Telegram 机器人,一旦出现高置信度的趋势机会,手机立刻收到提醒
📊 Metric notes
6 items
Registration history
5y 5m
Created at 2021-05-30 09:28
Audience scale
214.2K
Follower count at the last collection.
Follower / following
214.2K / 461
Followers >> following · Followers far outnumber following — a strong structural signal. Ratio: 465.
Posting evidence
30 collected
Latest collected posts become the basis for content and risk interpretation.
Profile density
Checkable profile evidence
Enough stored structure and content samples — no empty-account penalty.
Community sample
0
Too thin for a platform conclusion.
🗺️ Identity map
- Kinks / themes
- Swinging & groupFrom hashtags and repeated wording
🧩 Judgment stack
Primary identity
Image seller
Amateur sharing
Content themes
Monetization path
Trust signals
Risk signals
🧭 Why this type
Profile: Saved server profile for @laobaishare. The visible score now blends the durable lookup result with collected X evidence, media inventory, audience structure, and interaction traces; risk remains separate.
Collected posts: 5 saved recent post(s)
Media evidence: 14 saved media asset(s)
Community: 0 public review signal(s)
Location is self-declared.
🪪 Credit signals4
Account nature
Amateur sharing
Based on saved profile state, 5 collected post(s), 14 media asset(s), and 0 public community signal(s).
Positive signals
Stable identity / Low mutual-promo risk
0 higher-weight review signal(s) and no public Photo Match attachment are currently available.
Risk signals
low
0 caution/risk review signal(s) and 1 pending governance item(s) are attached.
Suitable for
Real X evidence is attached for @laobaishare, so the profile no longer depends on a pure lookup-time identity guess.
Not enough reviews yet.
🎬 Content experience
68/100Visual appeal
7.3
Exposure level
Unknown from public sample
Stimulation
6.9
Originality
6.8
Update stability
5.0
Paid-match confidence
8.0
📡 Platform signals
P1Following circle
thinAnalyzed
0
Priority candidates
0
Review queue
0
From accounts this handle follows; review-queue means lower priority only.
Open graph viewSite behavior
thin7d views
0
Favorites
0
Reports
0
Photo Match
Verification records
No live public Photo Match result is attached yet.
Use Photo Match when someone needs to prove that a specific photo or teaser video matches the person who appeared at verification time.
Community stance
How the crowd currently leans
No community signals yet — the first tracked review will appear here.
🪞 Identity signals
🧮 Score detail
10 items
Featured media archive
Narrative fallback🏛️ Evidence stack
0 archive cards · 2 timeline notes
0 archive card(s), 2 timeline note(s), and 0 approved review(s) currently back this score.
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