{"id":"W2006775383","doi":"10.1167/10.14.27","title":"Automaticity of online control processes in manual aiming","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Cursor (databases); Jump; Computer science; Artificial intelligence; Computer vision; Physics","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":[0.001249139,0.0004062645,0.000425665,0.0006606898,0.0002267241,0.001036852,0.0005382308,0.0004746608,0.002114363],"category_scores_gemma":[0.01378295,0.0004036833,0.0003103222,0.0003277605,0.0006496722,0.001087443,0.0007342555,0.0006695431,0.0003280775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003179247,"about_ca_system_score_gemma":0.0003850411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000778439,"about_ca_topic_score_gemma":0.0005102742,"domain_scores_codex":[0.9986401,0.0002782606,0.0001151903,0.0003515109,0.0004679159,0.0001469474],"domain_scores_gemma":[0.9912544,0.0047713,0.001655581,0.001413665,0.0006057766,0.0002993314],"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":[0.001755097,0.0004383316,0.02966803,0.0003579051,0.0001605331,0.0002651731,0.001619936,0.006019196,0.7788703,0.00707153,0.0004789282,0.173295],"study_design_scores_gemma":[0.0003017922,0.001468139,0.7872967,0.00008975111,0.0001466468,0.0009833255,0.0003464363,0.07211304,0.1115544,0.02343149,0.002046218,0.0002221084],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9568774,0.0003068807,0.03614081,0.00008767761,0.00004755552,0.00006474758,0.00009751164,0.0005528221,0.005824536],"genre_scores_gemma":[0.9958442,0.00005734079,0.003373993,0.00002208255,0.00001804647,0.00003793447,0.0000546271,0.00006707289,0.0005247641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002114363,"threshold_uncertainty_score":0.007073224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01884390464846127,"score_gpt":0.3138893385259878,"score_spread":0.2950454338775266,"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."}}