Cluster 4: evaluation · cell · unobserved
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Unobserved mediators do not disappear from a network
A Japanese essay on the difference between edges inferred from observed variables and the molecular interactions behind them. It links the mathematics of eliminating a mediator, a reproducible synthetic example, chemical-mediated microbial interactions, single-cell gene regulatory networks and mechanism assessment in drug discovery. It makes no claim about any real organism or drug.
When a model fails to beat the baseline, what should we measure next?
A Japanese essay on separating limitations of data, models and evaluation in perturbation prediction. Original analytical examples illustrate sampling-time identifiability and signal dilution; recent studies inform a practical measurement audit. This is not a reanalysis of empirical cell data.
When shrinking totals hide growing lesions: an audit of public CT data
Two-timepoint lesion volumes from 276 patients reveal heterogeneous changes hidden by aggregation. This analysis examines measurement selection and within-patient organ contrasts, not causal drug effects or RECIST progression.
Does a model that predicts well understand the mechanism? Separating prediction from mechanistic inference
A Japanese essay distinguishing observational prediction, prediction under intervention and mechanistic claims, drawing on recent perturbation-prediction benchmarks and ICH M15. A reproducible synthetic indirect-response example shows that parameter sets compatible with the same data agree on a slowly varying regimen but diverge in the unobserved early hours, and that early sampling resolves the practical non-identifiability. It makes no claim about any real drug.
What did the Virtual Cell predict? Target genes and evaluation shortcuts
A Japanese review of perturbation forecasting, target-gene masking and recent benchmarks, with a reproducible synthetic example distinguishing evaluation shortcuts from downstream prediction. The example does not establish real-data performance or the superiority of pairwise masking.