REVISION 01 ACCEPTED ON DEVELOPMENT
logistic C: 1 → 10
Development macro AP: 0.05999 → 0.07051
The agent reduced regularization. The numerical evaluator accepted the measured gain.
Built in approximately six hours
An autonomous research lab that learns from every experiment. Built from real FGFR data, with a measured ranking improvement in six hours.
Preclinical research · Khalifa Ibrahim · Solo builder
The evaluator owns the rules
Nemotron proposes. Numerical tools train. The evaluator decides.
Selection complete → freeze + commit predictions → held-out evaluation → ledger → frontend.
Two autonomous proposals
REVISION 01 ACCEPTED ON DEVELOPMENT
logistic C: 1 → 10
Development macro AP: 0.05999 → 0.07051
The agent reduced regularization. The numerical evaluator accepted the measured gain.
REVISION 02 REJECTED ON DEVELOPMENT
RBF scale: 20 → 40
Development macro AP: 0.07051 → 0.06128
The wider positional features scored worse. Revision 1 stayed in place.
A working autonomous loop: propose → fit → evaluate → retain or reject.
The complete record includes the later final-test outcome.
Measured FGFR2 high-activation improvement
| Same fitted sequence classifier | Mean-fold AP ↑ | High hits / 26 | Strong hits / 7 |
|---|---|---|---|
| Sigmoid probability ranking | 0.09732 | 1 | 0 |
| Raw decision-margin ranking | 0.11135 | 4 | 0 |
Same classifier. Better numerical ranking.
Raw margins restored ordering lost to 136 probabilities tied at 1.0. +0.01402 absolute AP.
2.92 seconds with cached features.
594 protected artifacts unchanged. The same 68-pick budget recovered 1 → 4 highly activating variants.
Development ranking repair implemented during analysis. The descriptive interval includes zero; independent validation is next.
Evaluation context / full history
v1 final macro average precision · higher is better
Bars share a zero baseline; scale ends at AP 0.12.
Final resistance AP: agent below the fixed reference.
This completed final test is retained in the evidence ledger.
The engineering claim
Our ambition: anticipate cancer’s escape routes through a continuous loop of biological models and real laboratory experiments.
Frozen ESM2 + numerical classifier
ESM2 provides biological representations; the classifier scores mutations; raw margins preserve ranking. Nemotron’s diagnostic tools inspect this pipeline’s aggregate results.
Persistent improvement / measured mechanism
Correct decisions on held-out synthetic diagnostic cases across four predefined failure families. A frozen rule interpreter evaluates the policy.
Nemotron selected two persistent rules: check saturation before ranking and feature shift before promotion. The independent referee accepted the revision.
A subsequent Nemotron run loaded that policy and inspected real FGFR aggregate evidence: rankings, scaling and sequence ablations.
5 calls · 10,024 tokens · 0 new fits
Sequence diagnostics + public reproduction
| FGFR2 representation | Mean AP | High hits / 68 picks | Decision |
|---|---|---|---|
| Current combined model | 0.11135 | 4 | Retained reference |
| Wild-type only | 0.11402 | 4 | Diagnostic |
| Mutation-delta only | 0.11377 | 5 | Diagnostic |
| Variance floor | 0.05951 | 2 | Rejected by gate |
668 variants · 3 reused folds · 12 fits. Branch ablations use different component counts; the default remains unchanged.
The six-hour headline, rebuilt from public data.
Fresh inputs and embeddings reproduce AP 0.09732 → 0.11135 and 1 → 4 high hits. Dependency installation excluded.
Our ambition: anticipate cancer’s escape routes through agents, biological models and prospective laboratory experiments.