{"id":"W3099546048","doi":"10.1101/2020.08.21.261198","title":"Suppression without inhibition: How retinal computation contributes to saccadic suppression","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Retinal Development and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft; Max-Planck-Gesellschaft; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Receptive field; Neuroscience; Saccadic masking; Retina; Surround suppression; Retinal waves; Parasol cell; Macaque; Photic Stimulation; Eye movement; Calcium imaging; Retinal; Retinal ganglion cell; Psychology; Biology; Visual perception; Perception; Intrinsically photosensitive retinal ganglion cells; Chemistry","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":[0.0001429877,0.0003249107,0.0001874736,0.0002475822,0.0001918157,0.0007051451,0.0002805523,0.0002836183,0.001405138],"category_scores_gemma":[0.0009003415,0.0001615258,0.0002187517,0.0001319154,0.0003097322,0.0004754571,0.0004068949,0.0002887705,0.0003555557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003535641,"about_ca_system_score_gemma":0.0003540252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001943559,"about_ca_topic_score_gemma":0.001005003,"domain_scores_codex":[0.9999046,0.00001195024,0.00000568328,0.00002060588,0.00003014502,0.00002692117],"domain_scores_gemma":[0.9996698,0.00009285814,0.00006723457,0.0000401505,0.00006161505,0.00006838798],"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":[0.0001871674,0.00003811144,0.003804747,0.00005040152,0.00001926313,0.0003789977,0.0001039414,0.01164022,0.9554993,0.01268834,0.0004069305,0.01518269],"study_design_scores_gemma":[0.00005044115,0.0002688678,0.06003422,0.00003238307,0.00007299364,0.0008050429,0.0001543964,0.650363,0.2470774,0.0376331,0.003448887,0.00005931252],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8950492,0.0004464631,0.08871548,0.0005507988,0.00007632898,0.00001951222,0.0001440145,0.0008944598,0.01410372],"genre_scores_gemma":[0.9967905,0.00007936471,0.002101647,0.000022985,0.000008932908,0.000004181833,0.00003328509,0.00004665718,0.0009125253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001943559,"threshold_uncertainty_score":0.00470072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01163733588880214,"score_gpt":0.2323221651317714,"score_spread":0.2206848292429692,"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."}}