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PGX — Lightweight Postgres for AI agents. Written in Rust. Thousands of isolated databases in one runtime. 🐘
翻譯準備中
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一分鐘完成驗證機器學習驗證Minor Planet Center的NEO確認頁面：對每個待確認的候選目標，預測其是真實近地天體的概率與偽陽性（偽像、衛星、恆星或主帶小行星）的概率，從而讓志願者後續觀測網路不在垃圾上浪費稀缺的望遠鏡時間。
AI 翻譯
Machine-learned vetting for the Minor Planet Center's NEO Confirmation Page: for every candidate awaiting confirmation, predict the probability it's a real near-Earth object vs. a false positive (artifact, satellite, star, or main-belt asteroid), so the volunteer follow-up network stops spending scarce telescope time on junk.
取自儲存庫 README
正在載入完整 README。 以下為已儲存的摘錄。
** Now has 2 other capabilities. Go to https://spacesift.vercel.app to see **
Machine-learned vetting for the Minor Planet Center's NEO Confirmation Page:
for every candidate awaiting confirmation, predict the probability it's a real
near-Earth object vs. a false positive (artifact, satellite, star, or main-belt
asteroid), so the volunteer follow-up network stops spending scarce telescope
time on junk. Only ~50% of NEOCP candidates are real NEOs today; in the
Rubin/LSST era that drops to ~8%.檢視完整 README ↗目前無法載入完整 README。請透過原文連結閱讀。 以下為已儲存的摘錄。
** Now has 2 other capabilities. Go to https://spacesift.vercel.app to see **
Machine-learned vetting for the Minor Planet Center's NEO Confirmation Page:
for every candidate awaiting confirmation, predict the probability it's a real
near-Earth object vs. a false positive (artifact, satellite, star, or main-belt
asteroid), so the volunteer follow-up network stops spending scarce telescope
time on junk. Only ~50% of NEOCP candidates are real NEOs today; in the
Rubin/LSST era that drops to ~8%.檢視完整 README ↗