402 lines
9.8 KiB
Markdown
402 lines
9.8 KiB
Markdown
# Extraction Log
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## 1. Purpose
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This file records model extraction events.
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Use it to track how models are extracted from articles, prompts, discussions, notes, and other source material.
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The extraction log helps preserve provenance.
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It answers:
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```text
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Where did this model come from?
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When was it extracted?
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What confidence level was assigned?
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What needs user review?
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What was promoted, rejected, merged, or deferred?
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```
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## 2. Entry Format
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Use this format for each extraction event:
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```md
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## YYYY-MM-DD — {Source Title}
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### Source
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```text
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title:
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path:
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author:
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source_type:
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date_written:
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```
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### Extraction Context
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```text
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reason_for_extraction:
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requested_by:
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extractor:
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mode: Model Mining Mode
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```
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### Extracted Models
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| Model ID | Model Name | Type | Confidence | Status | Proposed Path | Notes |
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| -------- | ---------- | ---- | ---------- | ------ | ------------- | ----- |
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### Non-Model Ideas
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```text
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-
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-
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-
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```
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### Skill Conversion Candidates
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```text
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-
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-
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-
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```
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### Agent Conversion Candidates
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```text
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-
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-
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-
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```
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### Runtime Usage Candidates
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```text
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-
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-
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-
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```
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### Open Questions
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```text
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1.
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2.
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3.
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```
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### Next Action
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```text
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```
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## 3. Confidence Levels
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Use:
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```text
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high
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medium
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low
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```
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### high
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The model is explicit, named, and structurally complete.
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### medium
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The model is strongly implied but not fully formalized.
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### low
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The model is plausible but requires user confirmation.
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## 4. Status Values
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Use:
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```text
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candidate
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draft
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active
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rejected
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merged
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deprecated
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archived
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```
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Default for implicit extractions:
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```text
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candidate
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```
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Default for structurally clear but unconfirmed extractions:
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```text
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draft
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```
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Use `active` only after user confirmation.
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## 5. Initial Extraction Notes
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## 2026-05-31 — Initial Known Model Seed
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### Source
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```text
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title: User-provided examples in CCPE System construction discussion
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path: conversation context
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author: Wantsong
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source_type: discussion
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date_written: 2026-05-31
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```
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### Extraction Context
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```text
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reason_for_extraction: Initialize model library with known model names mentioned by user.
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requested_by: Wantsong
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extractor: CCPE Forge planning process
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mode: Model Mining Mode
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```
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### Extracted Models
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| Model ID | Model Name | Type | Confidence | Status | Proposed Path | Notes |
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| ----------------- | ------------------------- | ---------------------------- | ---------- | --------- | --------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
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| cognitive-imaging | 认知显影 / Cognitive Imaging | intermediate; workflow-model | high | active | model-cards/intermediate/cognitive-imaging-model.md | Promoted after source review, Lite regression tests, and user confirmation. |
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| giant-cognition | 巨人认知 / Giant Cognition | applied | high | candidate | model-cards/applied/giant-cognition-model.md | Source material provided and Model Card created on 2026-06-01. |
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| cognitive-prism | 认知棱镜 / Cognitive Prism | intermediate; applied | medium | candidate | TBD | Mentioned as an existing review model. Source material needed. |
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### Non-Model Ideas
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```text
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- CCPE Forge as Creator / Auditor / Refactor / Model Mining Skill
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- Review Committee as possible Hybrid Runtime
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- Human-in-the-loop as design principle
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```
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### Skill Conversion Candidates
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```text
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- cognitive-imaging.skill.md
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- prediction-error-capture.skill.md
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- do-operator-test.skill.md
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- model-mining.skill.md
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```
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### Agent Conversion Candidates
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```text
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- cognitive-imaging-practitioner.agent.md (deferred)
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- review-committee-chair.agent.md
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```
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### Runtime Usage Candidates
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```text
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- review-committee.runtime.md
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- modeling-committee.runtime.md
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- article-to-model-extraction.runtime.md
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```
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### Open Questions
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```text
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1. Should Cognitive Imaging be marked active after full Model Card creation?
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2. Should Cognitive Prism be extracted from source articles before indexing further?
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3. Should prediction-error-capture be a separate Model Card or only a Skill under Cognitive Imaging?
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```
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### Next Action
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```text
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Create full Model Card for Cognitive Imaging from source material.
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Then run Model Mining Mode on source articles for Cognitive Prism.
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```
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## 2026-06-01 — 认知显影 Model Card Promotion
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### Source
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```text
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title: 大脑暗房：关于洞察力的显影术; 认知显影者1.1
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path: workbench/raw/2026-01-06-the-darkroom-of-brain.md; workbench/raw/认知显影者1.1.md
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author: Wantsong
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source_type: article; legacy agent prompt
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date_written: 2026-01-06; unknown
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```
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### Extraction Context
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```text
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reason_for_extraction: Promote the stable embedded cognitive model behind 认知显影者 Lite into a canonical Model Card and update the active Model Index.
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requested_by: Wantsong
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extractor: CCPE Forge
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mode: Model Mining Mode
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```
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### Extracted Models
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| Model ID | Model Name | Type | Confidence | Status | Proposed Path | Notes |
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| -------- | ---------- | ---- | ---------- | ------ | ------------- | ----- |
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| cognitive-imaging | 认知显影 / Cognitive Imaging | intermediate; workflow-model | high | active | model-cards/intermediate/cognitive-imaging-model.md | Stable named model. Active Lite prompt exists at agents/lite/cognitive-imaging-practitioner.prompt.md. |
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### Non-Model Ideas
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```text
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- 认知显影 as a Web-style expert prompt.
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- Article review committee as a future orchestration pattern.
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- Scenario probe as a CCPE classification prerequisite.
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```
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### Skill Conversion Candidates
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```text
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- cognitive-imaging.skill.md
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- prediction-error-capture.skill.md
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- causal-exposure-test.skill.md
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```
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Skill conversion is deferred. It should happen only if Codex automatic invocation or cross-agent method reuse becomes necessary.
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### Agent Conversion Candidates
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```text
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- cognitive-imaging-practitioner.agent.md
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```
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Agent conversion is deferred. The active production artifact is currently the Lite prompt.
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### Runtime Usage Candidates
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```text
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- article-review-committee.runtime.md
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- modeling-committee.runtime.md
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```
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Runtime design is deferred until the other review or modeling agents are upgraded.
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### Open Questions
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```text
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1. Should prediction-error-capture become a separate Skill later?
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2. Should causal-exposure-test be generalized as a reusable evaluation Skill?
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3. Which future committee should first consume 认知显影 as a formal Agent node?
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```
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### Next Action
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```text
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Keep 认知显影 active as Model Card + Lite Prompt.
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Do not create Skill, Agent Spec, or Runtime until scenario demand appears.
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```
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## 2026-06-01 — 巨人认知 Model Card Creation
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### Source
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```text
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title: 构建你自己的巨人 2.0; 巨人认知智能体2.2
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path: user-provided pasted text; agents/lite/giant-cognition.prompt.md
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author: Wantsong
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source_type: article; legacy agent prompt
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date_written: 2025-11-27; 2026-03-06
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```
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### Extraction Context
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```text
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reason_for_extraction: Refactor the existing 巨人认知智能体 into a portable Lite prompt and a single Model Card for the application-oriented cognitive review model.
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requested_by: Wantsong
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extractor: CCPE Forge
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mode: Refactor Mode + Model Mining Mode
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```
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### Extracted Models
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| Model ID | Model Name | Type | Confidence | Status | Proposed Path | Notes |
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| -------- | ---------- | ---- | ---------- | ------ | ------------- | ----- |
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| giant-cognition | 巨人认知 / Giant Cognition | applied | high | candidate | model-cards/applied/giant-cognition-model.md | User confirmed the model should remain a single Model Card. 双循环罗盘 and 五层甲板 are internal mechanisms, not separate Model Cards. |
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### Non-Model Ideas
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```text
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- 巨人认知 as a Web-style expert review prompt.
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- 双循环罗盘 as the internal dynamic mechanism of 巨人认知.
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- 五层甲板 as the internal layered diagnostic structure of 巨人认知.
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- 思想考古学家 as a GL3-oriented review stance inside the model.
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```
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### Skill Conversion Candidates
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```text
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- giant-cognition-review.skill.md (deferred)
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```
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Skill conversion is deferred. It should happen only if Codex automatic invocation or cross-agent method reuse becomes necessary.
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### Agent Conversion Candidates
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```text
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- giant-cognition.agent.md (deferred)
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```
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Agent conversion is deferred. The current production artifact is the Lite prompt.
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### Runtime Usage Candidates
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```text
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- review-committee.runtime.md
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```
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Runtime design is deferred until multiple review agents are upgraded and their collaboration contracts are clear.
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### Open Questions
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```text
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1. Should 巨人认知 become active after user review of the Lite prompt and Model Card?
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2. Should future review committee design treat 巨人认知 as one committee member or as a shared review model?
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3. Should 《构建你自己的巨人 2.0》 later yield a broader foundational model, separate from this applied review model?
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```
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### Next Action
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```text
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Review generated files:
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- agents/lite/giant-cognition.prompt.md
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- model-cards/applied/giant-cognition-model.md
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If approved, promote giant-cognition from candidate to active.
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```
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## 6. Maintenance Rules
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When a new extraction is performed:
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```text
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1. Add an entry with date and source.
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2. Record all extracted models.
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3. Record confidence level.
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4. Record status.
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5. Record proposed Model Card path.
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6. Record Skill / Agent / Runtime conversion candidates.
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7. Record open questions.
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8. Update model-index.md.
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9. Update model-dependency-map.md if relationships are known.
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10. Update model-usage-map.md if usage is known.
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```
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## 7. Final Rule
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The extraction log should make model formation traceable.
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A model without provenance is harder to trust, harder to revise, and harder to integrate.
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