--- title: "Ecosystem update — September 2026" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Ecosystem update — September 2026} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ## Python-native extension outside the frozen R contract 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 push workflow families, 12/12 OS/Python matrix lanes, 782/782 tests, 14,015/14,015 statements, and 6,757/6,776 raw branches (99.7196%). The 19 remaining branch arcs are the unchanged audited structural-debt set, with zero unexpected, stale, or unaudited debt. - [Crossed participant–item random-slope guide](https://stefanosbalaskas.github.io/gpbiometricspy/methods/crossed-random-slopes-location-scale/) - [gpbiometricspy PR #129](https://github.com/stefanosbalaskas/gpbiometricspy/pull/129)