{"id":"W4225900883","doi":"10.1101/2021.03.30.437692","title":"Dynamical processing of orientation precision in the primary visual cortex","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research; Agence Nationale de la Recherche","keywords":"Visual cortex; Orientation (vector space); Computer science; Computer vision; Artificial intelligence; Neuroscience; Psychology; Mathematics; Geometry","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":[0.0001926655,0.000181754,0.0002262087,0.0002593051,0.0001258987,0.0004527118,0.0001984934,0.0002126981,0.0004424555],"category_scores_gemma":[0.001322749,0.0001707202,0.0001774368,0.0001880513,0.0004153449,0.0003572551,0.0003579509,0.0002417183,0.0001224277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004396185,"about_ca_system_score_gemma":0.0002158162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001667318,"about_ca_topic_score_gemma":0.001197811,"domain_scores_codex":[0.9998761,0.00001410155,0.000005613138,0.00004196101,0.00003763496,0.00002455511],"domain_scores_gemma":[0.9998327,0.00005035146,0.00004204371,0.0000280297,0.00002912399,0.00001770899],"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":[0.0001485122,0.00002627343,0.008312613,0.0000798387,0.0000392446,0.0001374211,0.0002453368,0.01371785,0.9392008,0.005025285,0.000259977,0.03280684],"study_design_scores_gemma":[0.00003057591,0.0002268291,0.5200172,0.00002454511,0.00006459859,0.000902746,0.0001796106,0.242107,0.2148289,0.01953691,0.002008938,0.00007217499],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9653536,0.0003656185,0.03201506,0.0001015734,0.00001090817,0.00001255777,0.0001203016,0.0001227581,0.001897565],"genre_scores_gemma":[0.9975522,0.00007743416,0.002023404,0.00001077893,0.000004398791,0.000004655683,0.0000486889,0.00001268667,0.0002657038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001667318,"threshold_uncertainty_score":0.00331521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02809989821276839,"score_gpt":0.2922638210667368,"score_spread":0.2641639228539684,"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."}}