The companion Python package gpbiometricspy now includes a fully exact-main-certified crossed participant–item Gaussian hierarchical location–scale model with one location random slope for each crossed factor.
This addition is intentionally outside the frozen
gpbiometrics 2.0.0 semantic-parity contract. It does
not add a new R export, modify the
gpbiometrics API, or change the scientific/release record
of this R package. The frozen R surface remains the reference against
which gpbiometricspy preserves 406/406 semantic parity;
the crossed random-slope model is later additive Python-native
development.
The new method estimates participant- and item-specific heterogeneity in conditional associations while retaining crossed residual-scale heterogeneity, explicit population-versus-conditional prediction semantics, fail-closed design checks, and deterministic reproducibility certificates. It is not a causal model, artifact detector, sensor-validity score, or latent-state inference engine.
Certified gpbiometricspy PR #129 is pinned to merge SHA
d078e0366ace49c3ebeb2f6800bad6394d70631e: 14/14 exact-main
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19 remaining branch arcs are the unchanged audited structural-debt set,
with zero unexpected, stale, or unaudited debt.