{"id":"W2087687060","doi":"10.1152/jn.00728.2009","title":"Visuomotor Velocity Transformations for Smooth Pursuit Eye Movements","year":2010,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Smooth pursuit; Eye movement; Reference frame; Frame of reference; Oblique case; Position (finance); Computer vision; Computer science; Torsion (gastropod); Artificial intelligence; Transformation (genetics); Communication; Psychology; Physics; Frame (networking); Anatomy; Classical mechanics; Medicine; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008709613,0.0001054186,0.0001918723,0.000114135,0.0001871258,0.00004355697,0.0003447289,0.00007385514,0.0002051435],"category_scores_gemma":[0.0003506906,0.00008458515,0.000136405,0.00012018,0.00007979976,0.00025466,0.00001964295,0.0003610116,0.00004749278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009387651,"about_ca_system_score_gemma":0.00005969136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.07776e-7,"about_ca_topic_score_gemma":3.425718e-7,"domain_scores_codex":[0.9990453,0.00007202288,0.0003583668,0.0001421905,0.0001843401,0.0001977419],"domain_scores_gemma":[0.9993011,0.000111484,0.0002548443,0.0001065774,0.0001227829,0.0001031909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001005646,0.0001093172,0.000001268641,0.00001478915,0.000002276662,0.000003984753,0.0001358801,0.00003065617,0.993407,0.0008559481,0.0001170082,0.005221317],"study_design_scores_gemma":[0.003377291,0.004718193,0.0183314,0.00003059316,0.00004665931,0.0001708723,0.00007679122,0.007127483,0.8391601,0.02203173,0.1044832,0.0004457039],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912297,9.628978e-7,0.005362274,0.0006926892,0.002334365,0.0001429093,0.00002182103,0.00002077203,0.0001945471],"genre_scores_gemma":[0.9948518,0.0000233998,0.001056744,0.003349167,0.0004578671,0.000006466352,0.000001299439,0.00001631219,0.0002370008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1542469,"threshold_uncertainty_score":0.3449283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04759877623010218,"score_gpt":0.3399349229197376,"score_spread":0.2923361466896354,"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."}}