# Extraction Log

## 1. Purpose

This file records model extraction events.

Use it to track how models are extracted from articles, prompts, discussions, notes, and other source material.

The extraction log helps preserve provenance.

It answers:

```text
Where did this model come from?
When was it extracted?
What confidence level was assigned?
What needs user review?
What was promoted, rejected, merged, or deferred?
```

## 2. Entry Format

Use this format for each extraction event:

```md
## YYYY-MM-DD — {Source Title}

### Source

```text
title:
path:
author:
source_type:
date_written:
```

### Extraction Context

```text
reason_for_extraction:
requested_by:
extractor:
mode: Model Mining Mode
```

### Extracted Models

| Model ID | Model Name | Type | Confidence | Status | Proposed Path | Notes |
| -------- | ---------- | ---- | ---------- | ------ | ------------- | ----- |

### Non-Model Ideas

```text
-
-
-
```

### Skill Conversion Candidates

```text
-
-
-
```

### Agent Conversion Candidates

```text
-
-
-
```

### Runtime Usage Candidates

```text
-
-
-
```

### Open Questions

```text
1.
2.
3.
```

### Next Action

```text
```

## 3. Confidence Levels

Use:

```text
high
medium
low
```

### high

The model is explicit, named, and structurally complete.

### medium

The model is strongly implied but not fully formalized.

### low

The model is plausible but requires user confirmation.

## 4. Status Values

Use:

```text
candidate
draft
active
rejected
merged
deprecated
archived
```

Default for implicit extractions:

```text
candidate
```

Default for structurally clear but unconfirmed extractions:

```text
draft
```

Use `active` only after user confirmation.

## 5. Initial Extraction Notes

## 2026-05-31 — Initial Known Model Seed

### Source

```text
title: User-provided examples in CCPE System construction discussion
path: conversation context
author: Wantsong
source_type: discussion
date_written: 2026-05-31
```

### Extraction Context

```text
reason_for_extraction: Initialize model library with known model names mentioned by user.
requested_by: Wantsong
extractor: CCPE Forge planning process
mode: Model Mining Mode
```

### Extracted Models

| Model ID          | Model Name                | Type                         | Confidence | Status    | Proposed Path                                       | Notes                                                                                              |
| ----------------- | ------------------------- | ---------------------------- | ---------- | --------- | --------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
| cognitive-imaging | 认知显影术 / Cognitive Imaging | intermediate; workflow-model | high       | draft     | model-cards/intermediate/cognitive-imaging-model.md | Model content partially provided in Cognitive Imaging Specialist example. Needs formal Model Card. |
| giant-cognition   | 巨人认知 / Giant Cognition    | intermediate                 | medium     | candidate | TBD                                                 | Mentioned as an existing model-backed agent. Source material needed.                               |
| cognitive-prism   | 认知棱镜 / Cognitive Prism    | intermediate; applied        | medium     | candidate | TBD                                                 | Mentioned as an existing review model. Source material needed.                                     |

### Non-Model Ideas

```text
- CCPE Forge as Creator / Auditor / Refactor / Model Mining Skill
- Review Committee as possible Hybrid Runtime
- Human-in-the-loop as design principle
```

### Skill Conversion Candidates

```text
- cognitive-imaging.skill.md
- prediction-error-capture.skill.md
- do-operator-test.skill.md
- model-mining.skill.md
```

### Agent Conversion Candidates

```text
- cognitive-imaging-specialist.agent.md
- review-committee-chair.agent.md
```

### Runtime Usage Candidates

```text
- review-committee.runtime.md
- modeling-committee.runtime.md
- article-to-model-extraction.runtime.md
```

### Open Questions

```text
1. Should Cognitive Imaging be marked active after full Model Card creation?
2. Should Giant Cognition and Cognitive Prism be extracted from source articles before indexing further?
3. Should prediction-error-capture be a separate Model Card or only a Skill under Cognitive Imaging?
```

### Next Action

```text
Create full Model Card for Cognitive Imaging from source material.
Then run Model Mining Mode on source articles for Giant Cognition and Cognitive Prism.
```

## 6. Maintenance Rules

When a new extraction is performed:

```text
1. Add an entry with date and source.
2. Record all extracted models.
3. Record confidence level.
4. Record status.
5. Record proposed Model Card path.
6. Record Skill / Agent / Runtime conversion candidates.
7. Record open questions.
8. Update model-index.md.
9. Update model-dependency-map.md if relationships are known.
10. Update model-usage-map.md if usage is known.
```

## 7. Final Rule

The extraction log should make model formation traceable.

A model without provenance is harder to trust, harder to revise, and harder to integrate.