{"id":"W4285089369","doi":"","title":"Torque prediction for active exoskeleton control using ProMPs","year":2022,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Exoskeleton; Torque; Computer science; Control (management); Direct torque control; Control theory (sociology); Engineering; Artificial intelligence; Simulation; Physics; Electrical engineering; Induction motor; Voltage","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0005254546,0.0005781896,0.0007438096,0.0002185842,0.0003335537,0.0005657343,0.0003530749,0.0005362503,0.003002685],"category_scores_gemma":[0.001089085,0.0003292123,0.0003137469,0.0002661227,0.0002334942,0.0003237561,0.0004963644,0.000492873,0.0005970508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001097191,"about_ca_system_score_gemma":0.0004010077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003276436,"about_ca_topic_score_gemma":0.002854235,"domain_scores_codex":[0.9998524,0.00003600374,0.00001358485,0.00003424455,0.00004399356,0.0000196916],"domain_scores_gemma":[0.9995958,0.0002077691,0.00004423496,0.0000361174,0.00009942903,0.00001676056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001093834,0.0002010189,0.001318502,0.0007909326,0.00008418812,0.0002502512,0.0001754057,0.648335,0.03304873,0.00319184,0.002101416,0.3094088],"study_design_scores_gemma":[0.00001853133,0.0001288579,0.0006322427,0.00002313397,0.000009516015,0.00002188545,0.00001174391,0.99502,0.002941321,0.0005105439,0.0006762026,0.000005960942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04457137,0.0003946574,0.9502052,0.0001807835,0.0001411291,0.00007967035,0.000104874,0.0007711197,0.003551187],"genre_scores_gemma":[0.9587971,0.0001981617,0.03689988,0.00004430534,0.00004732174,0.0001063427,0.00009569361,0.00004525798,0.003765831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003276436,"threshold_uncertainty_score":0.01004493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01822616551690266,"score_gpt":0.2661099048030994,"score_spread":0.2478837392861968,"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."}}