{"id":"W4390722065","doi":"10.1101/2024.01.04.24300722","title":"Digital gait outcomes for ARSACS: discriminative, convergent and ecological validity in a multi-center study (PROSPAX)","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Genetic Neurodegenerative Diseases","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Université de Sherbrooke","funders":"Ministero della Salute; Else Kröner-Fresenius-Stiftung; Servier; Eberhard Karls Universität Tübingen; Ionis Pharmaceuticals; Deutsche Forschungsgemeinschaft; Eli Lilly and Company","keywords":"Gait; Physical medicine and rehabilitation; Discriminant validity; Convergent validity; Medicine; Psychology; Physical therapy; Psychometrics; Clinical psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009753949,0.0006968105,0.0009768853,0.001630158,0.0008591114,0.0008553565,0.0006401355,0.0005795979,0.001505322],"category_scores_gemma":[0.009470949,0.0002433976,0.001322438,0.001654457,0.0009137038,0.0006277637,0.001423758,0.0003356492,0.0002760055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005499272,"about_ca_system_score_gemma":0.0009866599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002306773,"about_ca_topic_score_gemma":0.005511278,"domain_scores_codex":[0.9930508,0.004145561,0.001010374,0.0009017549,0.0006658775,0.0002255966],"domain_scores_gemma":[0.9902393,0.002663797,0.003716585,0.001082962,0.001609396,0.0006879701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00241369,0.000279691,0.991339,0.0002570986,0.0009294002,0.00005984394,0.0001823195,0.0001004819,0.0003237317,0.00006021255,0.0001351916,0.003919257],"study_design_scores_gemma":[0.0005061777,0.002266274,0.995699,0.00007396668,0.0003488992,0.0001569978,0.0001944919,0.0001774316,0.0001749305,0.00006512577,0.0003267113,0.000009973405],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968007,0.0008102891,0.0004667964,0.00003970905,0.00001111112,0.0003977697,0.0009556366,0.000006818445,0.0005110218],"genre_scores_gemma":[0.9972676,0.0001261741,0.0007220135,0.00004096487,0.00001401613,0.0004435892,0.001272683,0.000002282025,0.0001106832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009753949,"threshold_uncertainty_score":0.05158442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.145067316399843,"score_gpt":0.3559222434420173,"score_spread":0.2108549270421742,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}