What problem does it solve? Turning identified research gaps and literature contradictions into rigorous, testable hypotheses is slow and inconsistent. This Skill converts gap analysis output into structured, falsifiable hypotheses with quantitative rejection criteria, evidence matrices, and multi-dimensional scoring. ## Core Features & Use Cases - Falsifiable Hypothesis Construction: Every hypothesis includes a statement, rationale, falsifiability test with quantitative rejection criteria, supporting and conflicting evidence, and a five-dimension composite score (novelty, plausibility, testability, clinical impact, feasibility). - Advanced Hypothesis Patterns: Built-in patterns for integration/framework hypotheses (Pattern #4), discriminative experiment design via phase-to-parameter mapping (Pattern #5), and co-primary recommendation strategies (Pattern #6). - Golden-Set Validation: Ships with five test cases (contradiction-driven, method gap, cross-domain analogy, empty input, multi-source) with semantic-equivalence expected outputs and a 0.70 pass threshold. - Use Case: A biomedical researcher finishing a gap analysis on PINN-based physiological modeling feeds the gaps in and receives ranked hypotheses with experiment designs, sample size estimates, and clinical translation paths. ## Quick Start Generate falsifiable, scored research hypotheses from my gap analysis output listing the identified research gaps and literature contradictions.
