yogsoth-ai
yogsoth-ai/de-anthropocentric-research-engine
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Strategy: Dialectic engine retuned for truth-seeking, not survival. A defender steelmans a claim into its MOST falsifiable form, a critic attacks to refute it, a judge classifies the exchange into BROKEN/CORROBORATED/UNFALSIFIABLE — the judge does NOT pick a winner or score persuasiveness. Methods: Irving debate (repurposed), Toulmin argumentation, Mayo severe testing.
Campaign: Logical extreme and boundary testing via reductio ad absurdum and edge-case analysis. Core question: Does this artifact collapse under logical limits and boundary conditions? Methods: Lakatos 1976, Dutilh Novaes 2016, BVA, Flyvbjerg Critical Case, Popper.
Campaign for mapping argument structures — extract claims, link evidence, assess strength, synthesize positions. Produces argument graphs in the wiki vault.
基于 SOC 职业分类
| name | leaderboard-harvesting |
| description | Systematically collect performance data from platforms and papers |
| execution | tactic |
| dependencies | {"sops":["discrepancy-identification","method-discovery","score-extraction"]} |
Harvest structured performance data from leaderboard platforms (Papers With Code, benchmark-specific sites), survey papers, and official benchmark repositories. Produces deduplicated, provenance-tracked score collections.
Identify and scrape all relevant leaderboard sources:
Yield: List of leaderboard URLs + initial method counts per source.
For methods not covered by leaderboards, extract scores directly from papers:
Yield: Raw score tuples with paper provenance.
Compare scores across sources for the same method-dataset-metric triple:
Yield: Validated score set with confidence annotations.
Consolidate all sources into a single canonical dataset:
Yield: Unified performance dataset ready for analysis.
| Metric | Floor |
|---|---|
| Leaderboard sources checked | 3 |
| Methods with scores | 15 |
| Cross-validated score pairs | 10 |
| Deduplication conflicts resolved | 5 |
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| discrepancy-identification | Compare same-method scores across sources, flag significant deviations |
| method-discovery | Identify all relevant methods via literature, leaderboards, citation chains |
| score-extraction | Extract (Task, Dataset, Metric, Score, Conditions) tuples from a paper |