{"id":"W4306673453","doi":"10.3390/vision6040062","title":"Reliable, Fast and Stable Contrast Response Function Estimation","year":2022,"lang":"en","type":"article","venue":"Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"CRFS; Contrast (vision); Poisson distribution; Duration (music); Spike (software development); Set (abstract data type); Computer science; Statistics; Mathematics; Artificial intelligence; Pattern recognition (psychology); Conditional random field","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":[0.002200737,0.00044584,0.0006596869,0.0008009998,0.0002423749,0.000606256,0.0005468414,0.0005935217,0.0007295565],"category_scores_gemma":[0.01456732,0.0002764303,0.000406763,0.000429363,0.0003295515,0.0009740614,0.0004683307,0.0005247824,0.0003161266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003783211,"about_ca_system_score_gemma":0.0005275815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001419417,"about_ca_topic_score_gemma":0.0009292734,"domain_scores_codex":[0.9989999,0.0002701256,0.00006114921,0.0002756176,0.0002684304,0.0001248608],"domain_scores_gemma":[0.9937564,0.004033441,0.0004096796,0.0008946852,0.0007904451,0.0001154458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001495025,0.0001642969,0.02044332,0.0003544994,0.0001531601,0.00041507,0.000299156,0.07480847,0.6419001,0.003978514,0.0005138007,0.2554745],"study_design_scores_gemma":[0.00006050709,0.0007452595,0.07216346,0.0000269543,0.00008987261,0.00140694,0.00009283113,0.5890597,0.3293846,0.004901787,0.001916483,0.0001515439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4056468,0.0004436386,0.5918359,0.0000495898,0.00001161968,0.00006064847,0.0002115546,0.001010405,0.0007297757],"genre_scores_gemma":[0.9217139,0.000089983,0.0775007,0.00001301665,0.000006885633,0.00005172289,0.0002235012,0.0001635547,0.0002365219],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002200737,"threshold_uncertainty_score":0.01163876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03033554312721178,"score_gpt":0.3081905401057173,"score_spread":0.2778549969785055,"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."}}