ModelRefs / Research AI Workflows
Research AI Workflows
Literature review, hypothesis generation, survey analysis and scientific writing assist.
Overview
Research workflows accelerate the read-synthesise-write loop with grounded retrieval, evidence grading and reviewer-mode drafting. The patterns below preserve provenance and citation so outputs are publication-ready.
Workflows in this category
- Literature Review — Run iterative literature reviews with deduplication, evidence grading and citation-ready synthesis.
- Hypothesis Generation — Generate and prioritise research hypotheses against a knowledge graph of prior work.
- Survey Analysis — Cluster open-ended survey responses, surface themes and quantify sentiment with citation to verbatims.
- Citation Graph Mining — Mine citation graphs for influential works, emerging clusters and high-leverage open questions.
- Dataset Curation — Curate, deduplicate and document research datasets with provenance and license tracking.
- Experiment Tracking Narrative — Convert experiment-tracker runs into reviewer-ready narratives with trade-off and next-step recommendations.
- Scientific Writing Assist — Draft, edit and citation-check scientific manuscripts with style-guide enforcement and reviewer mode.
- Peer Review Assist — Assist peer reviewers with structured weakness analysis and citation-grounded comparison to prior work.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Research AI Workflows.