Operon AISCIENTIFIC PLANNING COPILOT
+ New Experiment

Workspace

All Experiments

Recent

  • Lactobacillus rhamnosus GG supplemen…
  • continuous cathode polarization at -…
  • Generatively redesigned T7-gp17 RBD …
  • activating Wnt signaling with ligand…
  • gene knockdown or knockout of [gene]…
  • overexpressing a protein in HEK293 c…

Operon AI · AI Scientist demo

Operon AI Guide

How To Use Operon AI

Watch the pipeline in order: intake confirmation, literature QC, evidence retrieval, plan generation, then internal QA.

1.Use the conversational intake chat to describe the intervention, model system, endpoint, and comparator in natural language.

2.Let Operon AI keep asking follow-ups until the planning brief is sufficient for a real protocol, budget, and validation design.

3.Review the synthesized hypothesis preview before starting analysis.

4.Read Literature QC before the plan appears, then inspect the final protocol, materials, timeline, and validation sections.

5.Treat the final draft as a quality-checked starting point for scientist review, not as unreviewed raw model output.

Status Glossary

pending

A record exists, but analysis has not produced a review-ready draft yet.

running

The pipeline is actively moving through intake confirmation, QC, planning, or internal QA.

completed

The pipeline finished and produced a review-ready draft after internal quality checks.

failed

A pipeline stage stopped with a persisted error. Review the failure reason before retrying.

ready

The latest draft passed internal QA and can be reviewed as a candidate plan.

legacy preview

This is a pre-pipeline record rendered for compatibility, not a full Operon AI run artifact.

Quality Score

90-100: unusually strong operational draft after internal QA.

70-89: usable draft with normal scientist review still recommended.

50-69: low-confidence draft that likely needs another repair pass or manual review.

0-49: high-risk draft that should be treated as a generation failure.

Novelty States

not found

Operon AI found no close prior protocol or paper match in the queried sources.

similar exists

Related work exists, but the hypothesis still appears meaningfully distinct in intervention, endpoint, or setup.

exact match

A close match already exists in the literature or protocol ecosystem. Treat the hypothesis as needing differentiation.