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研究RES-2026-0103v0.1

能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件

第 09–10 篇與 v0.2 Experiment A 儀器。系統 =(模型,鷹架向量);單次品質 Q_SP 與完整系統品質 Q_F 給出鷹架存活率 SSR = Q_SP/Q_F、依賴率 SDR、鷹架成本倍率 SCM 與受控消融階梯 A0…A5 上的邊際鷹架產率——全部要跟物理額外成本一起讀,因為 LOOP 不是作弊,隱藏成本才是。第 10 篇把品質、語意工作、物理計算與鷹架封裝成 canonical intelligence event,在「不過早純量化」規則下用 Pareto 前沿比較系統,並固定最低報告標準。這條線的第一個真實數據點是 2026-09-03 在本地 9B 模型上的 pilot。

研究狀態
EXPERIMENTAL 正在進行實驗驗證
證據等級
E2 受控實驗
版本
0.1
更新
2026-09-07
建立
2026-09-02
領域
Evaluation, Agent Systems, Computation
計畫
PRG-2026-0101 智能的物理計量(IPM)
作者
Neo.K (EveMissLab)
AI 協作
Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)

研究問題

research_questions
  • Of a final answer, how much came from the model's native single pass and how much from retries, sampling, verifiers, tools, memory and planners — at what physical cost?
  • Does a stable scaffolding response curve exist for a fixed model and task set, and where does it enter the brute-force region?
  • Can two systems with the same final quality be told apart by capability source and physical cost rather than by a leaderboard score?

主張

claims
  • System capability ≠ model-native capability; Pass@k ≠ Pass@1; tool access ≠ tool utilization intelligence; invisible output ≠ zero cost.
  • SSR/SDR describe the structure of an intelligence source, not a defect; they must be read with SCM and the scaffolding physical overhead.
  • Intelligence is not any single element of the tuple (task, quality, semantic work, physical computation, scaffolding, metadata); the research object is the relation P_compute → N_μ → 𝔔.
  • First real pilot (three easy tasks, local 9B, 2026-09-03): SSR = 1.0 with a 3.1× device-energy multiplier from A0 to A5 — and the instrument's quality axis turned out to measure output-format compliance on two of the three tasks.

限制

limitations
  • One model, three tasks, two replicates, same-model verifier, code quality unmeasured, gate INCOMPLETE — a dataset for instrument revision, not an estimate.
  • Shapley-style scaffold attribution, information-matched tool controls and the 900-trial physical comparison are all still ahead.

關係

來源關係目標狀態ID
RES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件belongs_toPRG-2026-0101 智能的物理計量(IPM)ACTIVEREL-2026-0355
RES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件extendsRES-2026-0101 執行與物理線——一個答案在回合、語意工作、能量與計算時空上的代價ACTIVEREL-2026-0356
RES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件extendsRES-2026-0102 品質線——不叫人打分數也能量成果品質ACTIVEREL-2026-0357
RES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件developsTHY-2026-0109 鷹架能力紀錄:SSR、SDR、SCM 與消融階梯ACTIVEREL-2026-0366
RES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件developsTHY-2026-0110 canonical intelligence event、Pareto 比較與不過早純量化ACTIVEREL-2026-0367
CLM-2026-0104 F4——鷹架分離belongs_toRES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件ACTIVEREL-2026-0386
CLM-2026-0105 F5——語意中間層效用belongs_toRES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件ACTIVEREL-2026-0388
PAP-2026-0109 拿掉 LOOP 還剩多少智能?:單次智能、鷹架依賴與隱藏計算成本reportsRES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件ACTIVEREL-2026-0423
PAP-2026-0110 一個答案值多少物理世界?:智能產率的統一計量框架reportsRES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件ACTIVEREL-2026-0427
PAP-2026-0111 IPM v0.1 Canonical Index:智能物理計量學系列總論、統一符號表與 v0.2 實驗入口reportsRES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件ACTIVEREL-2026-0433
SYS-2026-0102 XA-04——A0→A5 模型執行器與鷹架調度器supportsRES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件ACTIVEREL-2026-0453
SYS-2026-0103 XA-06——真實模型 pilot 閘supportsRES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件ACTIVEREL-2026-0456
SYS-2026-0104 XA-06L——本地真實模型執行交接包supportsRES-2026-0103 能力線——拿掉 LOOP 還剩多少智能,以及統一的智能事件ACTIVEREL-2026-0459

歷史與來源歷程

Canonical URL
https://evemisslab.com/ai/research/RES-2026-0103/
機器可讀
/ai/research/RES-2026-0103/index.json
快照
AI-SNAPSHOT-v0.1-fe85b9694a45
來源歷程
source
EveMissLab research collection: Intelligence Physical Metrology (真本體論13)
extracted_by
Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports
extracted_at
2026-09-11
generator
tools/extract_all.py
claim_boundary
status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports