FROM SCORES TO ACTIONS: CERTIFIED PROMOTION AND K > 2 CONTROL OF JOINT TIME-SERIES GENERATORS

Joint time-series generators should create new trajectories while allowing rela- tionships to evolve and protecting what a task requires. We call this goal selective structural fidelity. It raises three distinct questions: are the generated paths plau- sible, is a requested change executed correctly, and is there evidence to adopt it? We develop a reference-aware evaluation contract that separates these questions. Our rank-adaptive K >2 path controller (KRPC) realizes matrix requests through thin products, with endpoint and complement preservation, basis covariance and explicit refusal. The evidence distinguishes execution from benefit. On a locked 2024 weather panel, event-preserving correction improves six quality measures over its calibrated reference; path conditioning also improves Energy and incre- ment Energy over a matched history-conditioned control. A distinct, locked 2025 expert policy improves Energy by 0.0600% over its protected reference, but does not lead the full roster. Rank-4 requests on K = 500 streamflow ensembles es- tablish high-dimensional execution. EEG and controlled decision studies expose quality–coverage and information limits. These are task-specific gains, not uni- versal dominance.