{"id":"W2917718064","doi":"10.1152/jn.00378.2018","title":"Discriminating between anticipatory and visually triggered saccades: measuring minimal visual saccadic response time using luminance","year":2019,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Canadian Institutes of Health Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Government of Canada; Stichting Jo Kolk Studiefonds","keywords":"Saccadic masking; Luminance; Saccade; Psychology; Eye movement; Context (archaeology); Saccadic eye movement; Saccadic suppression of image displacement; Artificial intelligence; Computer vision; Computer science; Neuroscience","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007771231,0.0004955496,0.0004822067,0.000759182,0.0001684866,0.000422933,0.0004091829,0.0005091116,0.00106186],"category_scores_gemma":[0.003919244,0.0002429503,0.0002419309,0.0002877517,0.0001875364,0.0004218258,0.0003238725,0.000471111,0.0003542261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002359535,"about_ca_system_score_gemma":0.00036391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009646482,"about_ca_topic_score_gemma":0.002317095,"domain_scores_codex":[0.9994004,0.0001112541,0.00004987058,0.0001948087,0.0001976587,0.00004599545],"domain_scores_gemma":[0.9980131,0.0009404595,0.0004570167,0.0001636328,0.0003005572,0.0001252322],"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":[0.0005508694,0.00006917182,0.01250065,0.0001949999,0.00005089778,0.00006718328,0.0001586851,0.0007482774,0.9309934,0.0001409787,0.0001306568,0.05439414],"study_design_scores_gemma":[0.0001322528,0.003264688,0.3443762,0.00006915523,0.0002192835,0.001313038,0.0002710039,0.05058729,0.5961362,0.001118695,0.002331906,0.0001802496],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6818346,0.0006325215,0.3144587,0.0000842705,0.00005885004,0.0001976942,0.0005121988,0.001136958,0.001084233],"genre_scores_gemma":[0.8712654,0.0002440359,0.126772,0.00006002303,0.00002977429,0.0004142719,0.0002937489,0.0001250816,0.0007956831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00106186,"threshold_uncertainty_score":0.004109859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09510766431955989,"score_gpt":0.353590009386931,"score_spread":0.2584823450673711,"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."}}