{"id":"W2083112975","doi":"10.1364/ao.39.000231","title":"Wiener-like correlation filters","year":2000,"lang":"en","type":"article","venue":"Applied Optics","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Sudbury","funders":"","keywords":"Wiener filter; Wiener deconvolution; Correlation; Optics; Filter (signal processing); Noise (video); Physics; Mathematics; Computer science; Algorithm; Artificial intelligence; Deconvolution; Blind deconvolution","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002428173,0.0001176322,0.00009788216,0.00003797107,0.00003527226,0.00002070454,0.0001409735,0.00008371925,0.0001036499],"category_scores_gemma":[0.000007967355,0.0001243723,0.00001990064,0.0001559337,0.00007974947,0.00008167922,0.00001890232,0.0001775779,0.0004820234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003914533,"about_ca_system_score_gemma":0.000002683316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.718006e-7,"about_ca_topic_score_gemma":3.420743e-7,"domain_scores_codex":[0.9994353,0.00000138011,0.0001270695,0.0001237788,0.00009128708,0.0002211837],"domain_scores_gemma":[0.9996484,0.00003684964,0.000009257819,0.0002604394,0.000008801709,0.00003623444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006159928,0.00001441977,0.0000326549,0.0000150258,0.00001808129,0.000005142903,0.00007266657,0.7964892,0.003359039,0.03143766,0.001828961,0.166721],"study_design_scores_gemma":[0.000701179,0.00003533299,0.0005081993,0.00002254531,0.00005029893,0.00001386718,0.0001504274,0.8903297,0.01388228,0.03515621,0.05833522,0.0008147351],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.274666,0.0002094269,0.3524204,0.0002373714,0.0005333901,0.0003701329,0.000009169427,0.007334791,0.3642193],"genre_scores_gemma":[0.8638418,0.0001238366,0.1354746,0.00008370814,0.00003173771,0.00002049861,0.00001098262,0.00003630614,0.0003765329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5891758,"threshold_uncertainty_score":0.6195596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005514409721956551,"score_gpt":0.1892525672340635,"score_spread":0.183738157512107,"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."}}