{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005371786,0.0006626968,0.000559421,0.0004161482,0.0002898636,0.0007140015,0.0009553587,0.001021366,0.002551602],"category_scores_gemma":[0.002889839,0.0003822453,0.0006153681,0.0003522455,0.0006689008,0.0005222997,0.0006113849,0.0008633651,0.0002305775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003774885,"about_ca_system_score_gemma":0.000589074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005697843,"about_ca_topic_score_gemma":0.004524517,"domain_scores_codex":[0.9998009,0.00006591259,0.00001771373,0.00003293636,0.00005739259,0.000025156],"domain_scores_gemma":[0.9988681,0.0007699021,0.00009133867,0.00009677842,0.000133507,0.00004037],"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":[0.00005191871,0.00004966137,0.0004785968,0.00007805412,0.00001229716,0.00003104435,0.00003972799,0.9945152,0.001819928,0.001280645,0.0001383856,0.001504431],"study_design_scores_gemma":[0.00001624378,0.0000302371,0.0001531238,0.00000903704,0.000005119126,0.000004125808,0.00001454403,0.9980611,0.0006069292,0.0007672549,0.0003276766,0.000004562891],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.594568,0.000362239,0.3857046,0.000587848,0.0002093478,0.0003793445,0.001324627,0.0008986041,0.01596542],"genre_scores_gemma":[0.9684737,0.000122968,0.02920897,0.00006801259,0.000009661722,0.000388589,0.0003625285,0.00004986121,0.001315707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005697843,"threshold_uncertainty_score":0.01132935,"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."}}