verdict-synthesis

To synthesize a scientific verdict, aggregate outputs from analytical modules like statistical power analysis and bias detection, then apply kill criteria and a severity matrix to generate a final critique with a confidence level.

A kill criteria matrix in research assessment is a predefined set of rules used to automatically reject scientific hypotheses that contain fundamental flaws, assigning severity levels to individual findings to aggregate an overall impact score.

Generate a structured JSON report from a hypothesis critique by synthesizing methodological and evidence-based module outputs into a unified verdict file, which runs alongside a markdown report detailing the decision.

Yes, you can use module aggregation to review a new drug trial hypothesis by synthesizing statistical, methodological, and feasibility checks into a clear recommendation like PROCEED, REVISE, PAUSE, or REJECT.

The best way to automate peer review for a research hypothesis is to consolidate analytical module findings into a coherent critique, applying a severity matrix to produce a final recommendation and confidence level.

You should not use automated verdict synthesis when you lack outputs from prerequisite analytical modules, as this process requires aggregating statistical, methodological, and evidence-based assessments to function correctly.