A reading notebook / Artificial intelligence × Science

AI for science,
read with care.

Original notes on models, experiments and the evidence that connects them. A quieter place to think about machine learning for scientific discovery.

EXPLORE THE NOTES
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The notebook
An opening collection

More reading notes

MODELS → EVIDENCE
02
Molecular science

A dataset split is a scientific experiment

The test set defines the kind of unfamiliarity a molecular model must handle. Choose that unfamiliarity before comparing scores.

04
Materials

The distance between a promising material and a usable sample

Candidate ranking is only one decision in a synthesis workflow. A useful evaluation follows the material into the laboratory.

05
Physics & simulation

What a physical constraint buys a learned surrogate

A small equation residual is evidence about one test. Reliable use also depends on boundaries, regimes, and accumulated error.

06
Earth & climate

Why weather skill needs a separate climate argument

Short-range predictive skill and long-term climate claims require different evidence, even when they describe the same atmosphere.

07
Research practice

Keeping controls inside an AI experiment loop

An adaptive system needs a record of its decisions and controls that survive adaptation. Otherwise, iteration can outrun inference.

The editorial lens

A useful model changes what we can test.
A useful experiment changes what we should believe.