Engineering the emergence of diagnostic information at the nano–bio interface: Supplementary Information (extended version) and code

Extended version of the Supplementary Information of the Comment “Engineering the emergence of diagnostic information at the nano–bio interface” by D. Pozzi and G. Caracciolo. The document derives the readout-space calibration (equation 1 of the Comment), states the assumptions under which it holds (linear response, equal covariance, censoring, pooling, batch effects) and verifies its main statements in simulation. It also sets out a worked path from calibration on healthy donors and pooled samples to cohort sizing and clinical validation. The Python script sim.py reproduces every number and Figure S1 from synthetic data, with a fixed random seed. The derivations and code were developed with a large language model (Claude, Anthropic) at the authors’ direction and verified by the authors.