{"id":"W3119910833","doi":"10.1109/tmrb.2021.3050512","title":"Robotic Rehabilitation and Assistance for Individuals With Movement Disorders Based on a Kinematic Model of the Upper Limb","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Robotics and Bionics","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada Foundation for Innovation","keywords":"Workspace; Kinematics; Context (archaeology); Robotics; Computer science; Trajectory; Artificial intelligence; Inverse kinematics; Rehabilitation robotics; Robot; Rehabilitation; Robot kinematics; Robotic arm; Physical medicine and rehabilitation; Human–computer interaction; Simulation; Mobile robot; Physical therapy; Medicine","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":[0.000224998,0.0001137363,0.0002316471,0.00007713371,0.0001074106,0.00001208496,0.00003737278,0.0001082051,0.00001827298],"category_scores_gemma":[0.0002204816,0.00006800412,0.0001197151,0.0001742368,0.0002113227,0.00002287655,0.000001337458,0.0001789049,2.723684e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003593867,"about_ca_system_score_gemma":0.0002647858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000198643,"about_ca_topic_score_gemma":0.00003935402,"domain_scores_codex":[0.9988707,0.00004777068,0.00026285,0.0002110483,0.0004851547,0.0001225097],"domain_scores_gemma":[0.9985421,0.0009621811,0.00006451442,0.0002007449,0.0001066793,0.0001238059],"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":[0.0004113118,0.001891853,0.004780372,0.001407455,0.0001609199,9.43713e-7,0.0003595483,0.9779256,0.0004891569,0.00239764,0.0001452778,0.01002992],"study_design_scores_gemma":[0.003044489,0.001812456,0.007662225,0.001141521,0.0002782355,0.000002990907,0.0004090686,0.9833695,0.0006711946,0.00140808,0.00007257921,0.0001276435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08295612,0.0001053575,0.8757033,0.04032956,0.0001828478,0.0006332349,0.00002773206,0.00001317998,0.00004863693],"genre_scores_gemma":[0.9469456,0.0002410951,0.05058089,0.001916117,0.00001123088,0.00004889512,0.000004849458,0.00001517028,0.000236144],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8639895,"threshold_uncertainty_score":0.2773128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01141995860591905,"score_gpt":0.2563992836484853,"score_spread":0.2449793250425663,"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."}}