{"id":"W4284887387","doi":"10.1109/tnsre.2022.3189038","title":"Predictive Simulations to Replicate Human Gait Adaptations and Energetics With Exoskeletons","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Exoskeleton; Replicate; Gait; Torque; Resistive touchscreen; Simulation; Work (physics); Controller (irrigation); Computer science; Energetics; Control theory (sociology); Engineering; Artificial intelligence; Physical medicine and rehabilitation; Physics; Mathematics; Mechanical engineering; Control (management); Computer vision; Statistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001147307,0.0001921984,0.000186144,0.0003183761,0.0004782369,0.00005295229,0.00006218279,0.00004412354,0.000008623078],"category_scores_gemma":[0.00001060969,0.0001876243,0.00004202601,0.0003911589,0.00005308388,0.0001118809,0.000003408031,0.0002473844,8.792202e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001042106,"about_ca_system_score_gemma":0.00001010461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002294639,"about_ca_topic_score_gemma":0.00001251263,"domain_scores_codex":[0.9989471,0.00004389429,0.0003147551,0.000278628,0.0002156347,0.0001999644],"domain_scores_gemma":[0.9991791,0.000342289,0.00003079402,0.0002184212,0.00007177831,0.000157639],"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":[0.000009475923,0.0000374884,0.00004597762,0.00008765037,0.00003182899,7.585458e-7,0.001302732,0.9896533,0.007590031,0.0007355164,0.00002356204,0.0004816356],"study_design_scores_gemma":[0.0003848992,0.001021618,0.002547468,0.00004740847,0.00003879056,0.00002146549,0.0009448947,0.9932579,0.0001403576,0.00003071131,0.001282591,0.0002818779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6189848,0.0001286113,0.378923,0.0003784896,0.0003880041,0.0006990239,0.0001501647,0.0003133221,0.00003454355],"genre_scores_gemma":[0.9968092,0.00001052314,0.00255357,0.00001825907,0.0000221999,0.000424115,0.000007621959,0.00005261866,0.0001018706],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3778244,"threshold_uncertainty_score":0.7651096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007142652016601482,"score_gpt":0.2033552088029908,"score_spread":0.1962125567863894,"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."}}