research

Automate hypothesis generation by defining a structured research goal, which triggers machine learning models to automatically generate and rank potential hypotheses. This reduces manual effort and streamlines the validation process for complex research datasets.

Pairwise Elo debate is a ranking mechanism where hypotheses are evaluated against each other to assign competitive scores. This automated debate process systematically identifies and elevates the strongest research hypotheses.

Integrate meta-review feedback by feeding it back into the research orchestration lifecycle, which refines the research direction and automatically adjusts future hypothesis generation. This ensures continuous improvement of research outcomes.

Yes, you need a structured vault for data storage and access to support the research lifecycle. This vault requirement ensures that goals, generated hypotheses, and debate data are organized and accessible.

Start automating the research lifecycle by creating a new goal or selecting an existing one using a goal slug. The system then orchestrates hypothesis generation, Elo debate ranking, and meta-review feedback automatically.