{"id":"W3006469780","doi":"10.1152/jn.00613.2019","title":"Reaching decisions during ongoing movements","year":2020,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Context (archaeology); Action (physics); Computer science; Internal model; Deliberation; Task (project management); Process (computing); Preference; Cognitive psychology; Movement (music); Point (geometry); Psychology; Control (management); Artificial intelligence; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002468745,0.00007750527,0.0001814857,0.00006387224,0.0001151372,0.00001960348,0.0002246674,0.00002264852,0.00002147679],"category_scores_gemma":[0.001734092,0.00006143618,0.00009571846,0.0001214757,0.0000233247,0.0001843807,0.00006000929,0.0002658553,0.00002833186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001206311,"about_ca_system_score_gemma":0.00002176255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001119331,"about_ca_topic_score_gemma":6.078062e-8,"domain_scores_codex":[0.9990421,0.0001524408,0.0003337888,0.0001507635,0.0001768299,0.0001440596],"domain_scores_gemma":[0.9992216,0.0002637895,0.0002871256,0.00007543323,0.00003654394,0.0001154691],"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":[0.0001380196,0.00002202294,0.00001035483,0.000003059308,0.000002982312,0.000192259,0.0001847618,0.002802124,0.9949406,0.0001012644,0.000004949357,0.001597582],"study_design_scores_gemma":[0.01057113,0.00620336,0.5563004,0.0002437263,0.00009241288,0.001131046,0.0003632068,0.05178222,0.3519526,0.005475859,0.01495806,0.0009259517],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977582,0.000006369081,0.0007343555,0.0009515003,0.0003063256,0.00004363633,0.000001313801,0.00001314243,0.0001851882],"genre_scores_gemma":[0.9959643,0.00005709375,0.0001675685,0.003403717,0.0003654297,4.935713e-7,9.943446e-8,0.00001056692,0.00003066424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.642988,"threshold_uncertainty_score":0.2505295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06030328987521991,"score_gpt":0.2741416108476148,"score_spread":0.2138383209723949,"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."}}