{"id":"W2946481393","doi":"","title":"Where's my hand? Updating proprioception and prediction for motor learning","year":2018,"lang":"en","type":"article","venue":"Journal of Exercise, Movement, and Sport (SCAPPS refereed abstracts repository)","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Efference copy; Proprioception; Psychology; Perception; Motor learning; Hand position; Coactivation; Efferent; Communication; Physical medicine and rehabilitation; Artificial intelligence; Computer science; Neuroscience; Afferent; Electromyography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007758999,0.0002259761,0.0002819378,0.0001667197,0.0001278116,0.0006912681,0.0003278227,0.0004921838,0.003180577],"category_scores_gemma":[0.0045345,0.0002204585,0.0001776027,0.0001141098,0.0006175081,0.001164691,0.0003563983,0.0007092499,0.0004939203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002445292,"about_ca_system_score_gemma":0.0004351354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001580534,"about_ca_topic_score_gemma":0.001722684,"domain_scores_codex":[0.999763,0.00005723234,0.00001462605,0.00008581079,0.00004293579,0.00003640467],"domain_scores_gemma":[0.9988285,0.0003909275,0.0003303367,0.0001694097,0.0001201849,0.0001607211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001815032,0.0007546414,0.1462743,0.0006265846,0.0002199638,0.0006910603,0.002907888,0.003721673,0.3978282,0.006109635,0.003320378,0.4357306],"study_design_scores_gemma":[0.0001261896,0.001341141,0.9041911,0.0002319988,0.0001806063,0.0007763433,0.001230092,0.01517649,0.0446473,0.02457895,0.007397665,0.0001220679],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813301,0.001298975,0.0102269,0.001230818,0.0001204005,0.00002940294,0.0001265797,0.0001248283,0.005511943],"genre_scores_gemma":[0.9925898,0.0002881531,0.005415879,0.0001216175,0.00002841079,0.00001677246,0.00005581613,0.00001959587,0.001463892],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003180577,"threshold_uncertainty_score":0.01064003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0163735776663438,"score_gpt":0.2402178989179866,"score_spread":0.2238443212516428,"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."}}