{"id":"W2950169708","doi":"10.1109/tnsre.2019.2917424","title":"A Mechatronic System for Studying Energy Optimization During Walking","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Army Research Office; Natural Sciences and Engineering Research Council of Canada","keywords":"Mechatronics; Computer science; Function (biology); Maxima and minima; Simulation; Energy (signal processing); Systems design; Energy cost; Control engineering; Engineering; Artificial intelligence; Physics; Mathematics","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":[0.0001425578,0.000164261,0.0002028786,0.0002167255,0.0002028584,0.00008633357,0.00006093249,0.00006387848,0.000003215247],"category_scores_gemma":[0.00002297532,0.0001537879,0.00009143947,0.0001776028,0.00001152644,0.000319483,9.884923e-7,0.00008907443,0.00000203251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001211339,"about_ca_system_score_gemma":0.000008793686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000251495,"about_ca_topic_score_gemma":0.000001531496,"domain_scores_codex":[0.9988461,0.00006614536,0.0003178242,0.0003692331,0.0001825864,0.0002181608],"domain_scores_gemma":[0.9991012,0.0005652467,0.00008460019,0.0001428822,0.00004400656,0.00006203553],"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":[0.00003208804,0.00001590319,0.000004465772,0.0004029972,0.000006762664,4.467012e-7,0.0002036961,0.8534188,0.1442525,0.001091511,1.849625e-7,0.0005706777],"study_design_scores_gemma":[0.0009501223,0.0002175855,0.0001195607,0.0001899039,0.00001617857,0.00001702813,0.0004308065,0.9922212,0.005627118,0.000002640276,0.00003734366,0.0001704509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3744701,0.0000516828,0.6233783,0.0000401525,0.00120331,0.0006501185,0.000009367249,0.0001847003,0.00001226771],"genre_scores_gemma":[0.9987701,0.000007718167,0.0006513583,0.000008561102,0.00005871607,0.000332389,9.098749e-7,0.00003335871,0.0001368908],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6243001,"threshold_uncertainty_score":0.6271288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008931257856182769,"score_gpt":0.1969824636951628,"score_spread":0.18805120583898,"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."}}