{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004269978,0.000231647,0.000572339,0.0003197107,0.0001971248,0.00007262408,0.0003012766,0.0001257384,0.00008029177],"category_scores_gemma":[0.001031128,0.0002019885,0.0001215773,0.0002631305,0.0001762585,0.0004342971,0.0001249029,0.0004964047,0.00006664815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004824005,"about_ca_system_score_gemma":0.0001476605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001205528,"about_ca_topic_score_gemma":3.881137e-8,"domain_scores_codex":[0.9971989,0.0009954978,0.0006684241,0.0003965952,0.000356817,0.0003838059],"domain_scores_gemma":[0.9981794,0.0007258437,0.0006801937,0.0001423883,0.0001071501,0.0001650123],"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":[0.001200172,0.00006239917,0.0002062475,0.00005104214,0.000006462944,0.00007184993,0.0004018872,0.00008589256,0.9958602,0.0000098153,0.000004309826,0.002039701],"study_design_scores_gemma":[0.003945251,0.009848721,0.2410429,0.00072592,0.0001941505,0.001537432,0.000525283,0.02878108,0.7114941,0.0004005518,0.0004920025,0.001012693],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990976,0.00002146128,0.0001684891,0.00007144211,0.0004586337,0.0001181288,0.00000457088,0.00002690174,0.00003275945],"genre_scores_gemma":[0.9986885,0.00002740757,0.0003732759,0.0004100663,0.0003392072,6.871859e-7,3.341366e-7,0.0000416729,0.0001188991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2843662,"threshold_uncertainty_score":0.8236852,"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."}}