hypothesis-typology

You classify scientific hypotheses by analyzing their structure, intervention claims, and prior trial context to assign one of five types (T1-T4, U1), enabling targeted critique and structured review.

Hypothesis classification categorizes a hypothesis into predefined types to determine relevant analytical modules like power analysis or bias detection, needed when an AI generates a new clinical trial hypothesis for detailed review.

Prioritize critique efforts by assigning the hypothesis to a specific category (T1-T4, U1), which defines the most relevant analytical modules required for a structured review process.

Yes, you can categorize interventional efficacy and target validation hypotheses by analyzing the hypothesis structure and intervention claims to determine the appropriate category and guide subsequent review.

Classification is limited to five predefined types (T1-T4, U1) and depends on the hypothesis structure and prior trial context, meaning unstructured or highly novel claims may be categorized as U1.

Prior trial context is analyzed alongside hypothesis structure and intervention claims to determine the most appropriate category, ensuring accurate classification for targeted critique efforts.