yogsoth-ai Evidence Mapping
Systematically build evidence maps to reveal structural gaps.
Operations
- concept-matrix-construction — articles × concepts coverage visualization
- gap-keyword-extraction — gap-indicating sentence identification
- evidence-grading — quality assessment of available evidence
- egm-construction — structured evidence gap map output
Available SOPs
Subagent: concept-matrix-construction, gap-keyword-extraction, evidence-grading, egm-construction Import: paper-overview, paper-search
Execution Guidance
Build concept matrix first (articles × concepts), identify empty cells as gap candidates, verify with keyword extraction from full texts, grade evidence quality in populated cells, construct final EGM for structural view.
Minimum Yield
<HARD-GATE>
- concept-matrix: >= 1 constructed
- gap-keyword passes: >= 3
- evidence grading: >= 5 items graded
- EGM: >= 1 constructed
</HARD-GATE>
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| concept-matrix-construction | Build articles × concepts coverage matrix to visualize research landscape and identify empty cells as gap candidates. |
| deep-insight-paper-overview | Paper metadata and abstract-level overview. Import of literature-engine/literature-overview skill. Abstracts only — no substantive claims without deeper reading. |
| deep-insight-paper-search | AI-powered paper summary and search. Import of literature-engine/literature-search skill. AI summary level — cite as "AI-extracted" not "paper states". |
| egm-construction | Build structured Evidence Gap Maps — define axes (intervention × outcome or method × domain), place gaps in cells, annotate with evidence density and quality. |
| evidence-grading | Assess evidence quality using GRADE/SOE framework. Rates certainty level and identifies downgrade reasons. |
| gap-keyword-extraction | Extract gap-indicating sentences and phrases from papers/reviews. Identifies linguistic markers of research gaps (e.g., "remains unclear", "has not been explored", "limited understanding"). |