{"id":"W2312824571","doi":"10.1152/jn.00975.2010","title":"The influence of predicted arm biomechanics on decision making","year":2011,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":193,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biomechanics; Movement (music); Kinematics; Physical medicine and rehabilitation; Task (project management); Computer science; Cognitive psychology; Trajectory; Process (computing); Psychology; Physics; Engineering; Anatomy; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007018411,0.00007409429,0.0001523814,0.00009898078,0.00009109481,0.000007400668,0.0003546148,0.00003542563,0.000009240085],"category_scores_gemma":[0.001292876,0.00004273445,0.00007646193,0.0001646881,0.00008381846,0.00009156384,0.00004062849,0.0001861789,0.000006494931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008050712,"about_ca_system_score_gemma":0.00003016796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000011617,"about_ca_topic_score_gemma":1.340708e-7,"domain_scores_codex":[0.9990008,0.0001624587,0.0003916692,0.0001116105,0.0002050753,0.0001283931],"domain_scores_gemma":[0.9984137,0.0007145017,0.0005602694,0.0001590294,0.0001185611,0.00003388258],"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":[0.000849928,0.00007194495,0.000002071637,0.000002245731,0.000003229479,0.00003549795,0.00008172378,0.001056148,0.9858649,0.001438768,0.00000483034,0.01058872],"study_design_scores_gemma":[0.00400656,0.0252684,0.5067232,0.0004736643,0.00009455137,0.0006472443,0.0001089944,0.02909805,0.3161071,0.1127174,0.004296673,0.0004582128],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988821,0.000005927552,0.0004066213,0.00005563823,0.0004851972,0.00006029279,0.000002458644,0.000006003246,0.00009583026],"genre_scores_gemma":[0.9990974,0.0001173461,0.0001442545,0.0005619058,0.00006343995,8.030502e-7,3.121199e-8,0.000007170111,0.000007614144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6697578,"threshold_uncertainty_score":0.174266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04018188276036089,"score_gpt":0.2683922349679754,"score_spread":0.2282103522076145,"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."}}