Skill 审计报告

policyengine-data 审计报告.

Load for PolicyEngine's data layer — how the microdata behind population microsimulations is built, calibrated, versioned, and named. Covers the Microcosm stack (Frame kernel, microcosm-fit conditional models, microcosm-calibrate weights with L0 sparsity, build/release gates), the certified datasets that flow into policyengine bundles (populace_us_2024 sparse ~57k default, populace_us_2024_acs_local ~1.6M local-area, populace_uk_2023 private), the "one national dataset filtered by geography" local-area philosophy, the calibration diagnostics dashboard, and where data work goes now that policyengine-us-data is archived. Triggers: Microcosm (formerly Populace), Frame, microcosm-fit, microcosm-calibrate, calibration target, survey weights, reweighting, imputation, QRF, quantile loss, L0 sparsity, sparse 57k, local-area data, ACS, FRS, WAS, enhanced microdata, DEFAULT_DATASET. NOT for: running simulations (see policyengine) or diagnosing a specific score mismatch (see policyengine-calibrat