score-and-rank

What problem does it solve?

Score-and-rank automates the critical early-stage decision in research pipelines by combining data feasibility with literature-informed signals to identify and select the top candidate research question for analysis.

Core Features & Use Cases

• Reads Stage 2 outputs (research_questions.json) and computes a composite score by blending data feasibility, novelty, and literature support, then ranks candidates.
• Supports a fast-track mode that reuses prior scoring details to skip web searches during rapid iteration.
• Outputs backward-compatible ranked_questions.json and detailed scoring results for downstream stages.
• Provides a structured selection_metadata block and progress tracking to support auditability and reproducibility.
• Useful for teams automating topic selection in health research pipelines, clinical data studies, or any workflow requiring reproducible candidate evaluation.

Quick Start

Invoke the score-and-rank process with your pipeline output folder to compute scores and select the top candidate.