Bayesian Multi-Modal Latent-State Inference for n=4 Deep-Space Crew Analogues: A Reproducible Methodology Pipeline for the NASA Artemis II Human Research Data Challenge

Abstract The Artemis II Human Research Data Methodology Challenge requires extracting reliable scientific insight from a dataset of four astronauts measured across three concurrent studies, with high-dimensional readouts and small effective sample size. Conventional point-estimate procedures are unreliable in this p >> n regime. We develop a reproducible methodology pipeline applied to the SpaceX Inspiration4 public archive (NASA OSDR studies OSD-569 through OSD-687, n=4 civilians, six timepoints L-92 to R+82) as a surrogate analogue. The pipeline combines (i) per-modality leave-one-subject-out (LOSO) baselines with Bayesian Beta-Binomial uncertainty bands; (ii) hierarchical Bayesian logistic regression with horseshoe shrinkage fit by NUTS; and (iii) a 2-dimensional shared-latent factor model fusing seven modalities (1110 features). Across nine modalities the LOSO accuracy spans 0.40-0.69; urine cytokines and 18 cardiovascular features are the most informative non-invasive surrogates (accuracy 0.688 and 0.679), establishing a feature-efficiency frontier in which 18 cardiovascular readouts equal 406 urine features in classification utility. The hierarchical Bayesian model recovers honest calibration (Brier 0.224, mean p_correct = 0.555, mean 95% credible-interval width 0.775 across four LOSO folds). Critically, although no individual biomarker survives multiple-testing correction (0 of 1112 features at Benjamini-Hochberg q<0.05), a label-permutation test shows that the fused multi-modal representation separates pre- from post-flight state significantly above chance (LOSO logistic accuracy 0.71; permutation p=0.026): multi-modal fusion recovers a spaceflight signature invisible to per-feature analysis. We additionally release a harmonised 24x1112 multi-modal master table aligning nine Inspiration4 modalities on a common subject-timepoint grid, as a reusable open data resource. Released openly as a post-challenge contribution to the NASA HRP community; the author is ineligible to compete under the America COMPETES Act.