{"id":"W4413140890","doi":"10.1097/wnr.0000000000002212","title":"Overlapping functional micro-organization of orientation and spatial frequency maps in the visual cortex","year":2025,"lang":"en","type":"article","venue":"Neuroreport","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visual cortex; Stimulus (psychology); Spatial frequency; Neuroscience; Orientation (vector space); Perception; Visual perception; Spatial organization; Orientation column; Pattern recognition (psychology); Computer science; Communication; Artificial intelligence; Psychology; Biology; Physics; Cognitive psychology; Mathematics; Striate cortex; Optics","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":[0.0001654733,0.00007048919,0.0000798763,0.0001089236,0.000104028,0.00004030265,0.00006339932,0.00003917982,0.00006343992],"category_scores_gemma":[0.0004180105,0.00005866048,0.0000150398,0.000523036,0.00005407326,0.0001239634,0.00002418964,0.00009923954,0.000003938172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001336804,"about_ca_system_score_gemma":0.00008116476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004181562,"about_ca_topic_score_gemma":0.000008628537,"domain_scores_codex":[0.9991215,0.00008127042,0.0002602705,0.0002472132,0.0002059755,0.00008375721],"domain_scores_gemma":[0.9996518,0.00006493416,0.0001223013,0.0000923829,0.0000541648,0.00001445476],"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":[0.000009558967,0.00005737834,0.03137535,0.00002254212,6.769029e-7,0.00001189528,0.0003258744,0.000005642841,0.9632548,0.003045585,0.00008682267,0.001803874],"study_design_scores_gemma":[0.000397781,0.0000826117,0.7935307,0.00002967765,0.00001112193,0.0000961605,0.0002121406,0.0003888135,0.2015525,0.003416732,0.0001915961,0.00009012468],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910365,0.000003421763,0.006515594,0.0002440036,0.0004158329,0.0001366239,0.000002716814,0.00002581987,0.001619427],"genre_scores_gemma":[0.9982337,0.00001128699,0.00004718805,0.001528671,0.00002853415,0.000004791264,0.00001535002,0.000006046197,0.0001244749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7621554,"threshold_uncertainty_score":0.2392105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0279999475157196,"score_gpt":0.3023027526095903,"score_spread":0.2743028050938707,"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."}}