{"id":"W2884526948","doi":"10.1371/journal.pone.0200621","title":"The fast contribution of visual-proprioceptive discrepancy to reach aftereffects and proprioceptive recalibration","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Gesellschaft für Erziehungswissenschaft; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Proprioception; Sensory system; Hand position; Physical medicine and rehabilitation; Visual feedback; Psychology; Task (project management); Computer science; Cognitive psychology; Neuroscience; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002468706,0.0004285641,0.0004740427,0.0002022409,0.0001427217,0.0002555918,0.000354851,0.0004017149,0.002141085],"category_scores_gemma":[0.002880679,0.0002537511,0.0002204628,0.000151257,0.0003579659,0.0003599426,0.000807758,0.0008553503,0.0002150732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001683924,"about_ca_system_score_gemma":0.0002018011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000555755,"about_ca_topic_score_gemma":0.0006688964,"domain_scores_codex":[0.999643,0.00004024235,0.00002766304,0.00006909989,0.0001477086,0.00007226518],"domain_scores_gemma":[0.9992487,0.0003330559,0.0001428961,0.0001187834,0.00005108639,0.0001053653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004234848,0.00007915417,0.001250521,0.0001044896,0.00001301695,0.00009271585,0.00006997706,0.0007587807,0.9845582,0.00008558982,0.00004715912,0.0125169],"study_design_scores_gemma":[0.00006414879,0.002063337,0.4581767,0.00005508686,0.0000380799,0.0009857399,0.0001791422,0.01066373,0.5259866,0.0005561321,0.001191855,0.00003952183],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924442,0.0003670799,0.005643016,0.00004710758,0.00002562504,0.00003411227,0.00004923235,0.0001682623,0.001221305],"genre_scores_gemma":[0.9977313,0.00008986283,0.001374512,0.0000224842,0.000004768181,0.00002838659,0.00005665362,0.00004309701,0.0006489522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002141085,"threshold_uncertainty_score":0.007162631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03012128449527226,"score_gpt":0.2561220307273332,"score_spread":0.2260007462320609,"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."}}