{"id":"W2037009445","doi":"10.1007/s00221-010-2458-1","title":"Automatic movement error detection and correction processes in reaching movements","year":2010,"lang":"en","type":"article","venue":"Experimental Brain Research","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Montréal","keywords":"Movement (music); Artificial intelligence; Psychology; Physical medicine and rehabilitation; Neuroscience; Computer science; Computer vision; Communication; Medicine; Physics; Acoustics","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":[0.001016246,0.0004735563,0.0003636656,0.0006866873,0.000296619,0.001113942,0.0004587972,0.0008248377,0.002622157],"category_scores_gemma":[0.01706186,0.0004522984,0.0002322805,0.0005598908,0.0007945085,0.001716831,0.0005324584,0.0009531793,0.0002677101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003751987,"about_ca_system_score_gemma":0.0005953795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001608788,"about_ca_topic_score_gemma":0.0012173,"domain_scores_codex":[0.9992062,0.0001828911,0.00006553522,0.0001828332,0.0002739273,0.00008854712],"domain_scores_gemma":[0.9913983,0.0064194,0.0009394362,0.0005147742,0.0005374475,0.0001905528],"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":[0.005135063,0.0005558756,0.0255975,0.0003759808,0.0001478895,0.0004490148,0.002252847,0.01178743,0.7363634,0.02364817,0.0006969689,0.1929899],"study_design_scores_gemma":[0.0002971472,0.0008272694,0.6779668,0.00006574106,0.0001192868,0.001612799,0.0004642832,0.161059,0.1040234,0.05189291,0.001541134,0.0001302292],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9675137,0.0004146102,0.02788619,0.0002242502,0.00007378039,0.00003533923,0.00008419278,0.0001150045,0.003652772],"genre_scores_gemma":[0.9946874,0.0001015513,0.004005401,0.00003236883,0.00002896174,0.00001962458,0.00006319156,0.00006663954,0.0009948484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002622157,"threshold_uncertainty_score":0.008772016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0703262100138157,"score_gpt":0.3832247252068089,"score_spread":0.3128985151929932,"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."}}