{"id":"W4406730860","doi":"10.1371/journal.pone.0292334","title":"Coordinated human-exoskeleton locomotion emerges from regulating virtual energy","year":2025,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Toronto Rehabilitation Institute; University of Waterloo","funders":"Division of Emerging Frontiers in Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Ontario Research Foundation","keywords":"Exoskeleton; Gait; Kinematics; Computer science; Physical medicine and rehabilitation; Torque; Simulation; Control theory (sociology); Artificial intelligence; Physics; Control (management); 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":[0.00005058013,0.00009976589,0.0001516632,0.00008684978,0.00007810296,0.00002222231,0.00008364362,0.00008293311,0.00007104746],"category_scores_gemma":[0.00003355108,0.0001068019,0.00003391889,0.0001760982,0.0000262488,0.0000468848,0.00002920854,0.00008926955,0.00001016036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004818075,"about_ca_system_score_gemma":0.000006588977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004344108,"about_ca_topic_score_gemma":0.00002161535,"domain_scores_codex":[0.9993904,0.00002132472,0.0002104186,0.000128663,0.0001173199,0.000131916],"domain_scores_gemma":[0.9996498,0.00005463817,0.00002376689,0.0001758727,0.00006473356,0.00003116391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001012147,0.0006891725,0.002736797,0.0001993817,0.0005312789,0.000001560742,0.0002988423,0.06121347,0.8845328,0.03929286,0.001707186,0.008786545],"study_design_scores_gemma":[0.00102323,0.0002151451,0.007852432,0.0008204113,0.0001899767,1.315313e-7,0.000173266,0.5354702,0.4364285,0.01634727,0.0009690387,0.0005103771],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9717222,0.0002585531,0.02383207,0.0003925459,0.0001601978,0.0000967017,0.00001014744,0.0003733718,0.003154197],"genre_scores_gemma":[0.9950996,0.00002963165,0.003013561,0.00003246038,0.00005216998,0.00001411983,0.00006345747,0.00002015504,0.001674835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4742567,"threshold_uncertainty_score":0.4355256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01455379371170605,"score_gpt":0.206661252726585,"score_spread":0.1921074590148789,"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."}}