{"id":"W2737044682","doi":"10.1007/s00426-017-0888-0","title":"Distinct and flexible rates of online control","year":2017,"lang":"en","type":"article","venue":"Psychological Research","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Canada Foundation for Innovation","keywords":"Kinematics; Motor control; Control (management); Computer science; Hum; Visual control; Artificial intelligence; Psychology; Neuroscience; Physics","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":[0.001566576,0.0002971502,0.0003532324,0.0007604264,0.0002770693,0.002525196,0.0008255741,0.0006253845,0.005010032],"category_scores_gemma":[0.01948388,0.0004306907,0.0004171561,0.0004715965,0.001205178,0.003004529,0.001509175,0.001516718,0.0006941725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004044129,"about_ca_system_score_gemma":0.0002962789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003713872,"about_ca_topic_score_gemma":0.0002863499,"domain_scores_codex":[0.9989173,0.000199778,0.00007482927,0.0003465935,0.0003114897,0.000149999],"domain_scores_gemma":[0.9887588,0.005867874,0.0009118767,0.00320552,0.0006140076,0.0006419526],"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":[0.002511619,0.0009531102,0.1011133,0.0004139356,0.0005279479,0.0003024983,0.005491247,0.01138309,0.2545392,0.3056567,0.002005653,0.3151017],"study_design_scores_gemma":[0.0001974519,0.0004294654,0.6883831,0.000116002,0.000207748,0.001324829,0.001171358,0.07317066,0.04425989,0.1854267,0.005087301,0.0002255021],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.915669,0.0005236263,0.05652275,0.000365039,0.00008266811,0.00005938062,0.0003663147,0.0002529292,0.02615835],"genre_scores_gemma":[0.9924513,0.0000840327,0.005313102,0.00004568652,0.00002495491,0.00003384805,0.0001112331,0.0001117189,0.001824099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005010032,"threshold_uncertainty_score":0.01676023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4253506869906766,"score_gpt":0.536507820487754,"score_spread":0.1111571334970774,"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."}}