A source-audited study of extrapolation: scale-ordered validation, alternative scaling-law families, predictive model selection, repeated data, dependence, and effective-data constraints.
A source-audited study of over-training, downstream metric behavior, lifecycle cost, measured serving demand, uncertainty-aware artifact selection, pilot gates, and a training authorization that hands release and rollback requirements to the serving and deployment modules.
A source-audited study of neural scaling experiments: measurement contracts, power laws, joint model-data loss surfaces, compute-optimal allocation, paper-contract comparison, fitting, and uncertainty.