{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001593952,0.0002202669,0.0001812874,0.0001584828,0.0001453286,0.000363752,0.0001035938,0.0001606417,0.001288133],"category_scores_gemma":[0.001102993,0.0001432253,0.0002870869,0.0001295474,0.0001728075,0.000188437,0.0002132179,0.0002764862,0.0002365586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002684718,"about_ca_system_score_gemma":0.0003249559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003694499,"about_ca_topic_score_gemma":0.001736307,"domain_scores_codex":[0.999929,0.00001746082,0.000004693851,0.00002120384,0.00001974126,0.000007999579],"domain_scores_gemma":[0.9998177,0.00009468989,0.00003016573,0.00002291849,0.00002502924,0.000009544324],"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":[0.0004604806,0.00009637271,0.007450623,0.0001462124,0.00005978556,0.0004069197,0.0005651925,0.2389359,0.6902506,0.01221905,0.0003868286,0.04902191],"study_design_scores_gemma":[0.00005645681,0.0002888044,0.04134181,0.00001807396,0.00003109402,0.0002748216,0.00007638329,0.8945882,0.05267487,0.009175147,0.001416146,0.00005817132],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.892437,0.0001359317,0.1044307,0.00005724574,0.00001510333,0.00004855289,0.0001604136,0.0003933637,0.002321668],"genre_scores_gemma":[0.9910081,0.00006203142,0.008267088,0.000004966427,0.000001827245,0.00002586962,0.0001128048,0.00002922215,0.0004882966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003694499,"threshold_uncertainty_score":0.007345974,"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."}}