{"id":"W2163146329","doi":"10.1109/icassp.2011.5946684","title":"Median filter with absolute value norm spatial regularization","year":2011,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Regularization (linguistics); Mathematical optimization; Mathematics; Linear programming; Minification; Algorithm; Linear filter; Filter (signal processing); Computer science; Artificial intelligence; Computer vision","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":[0.0002689855,0.00008979834,0.00008893452,0.00006787012,0.00007237443,0.0000796989,0.0004125476,0.00004179345,0.0001472708],"category_scores_gemma":[0.00001657976,0.00006340791,0.00002578537,0.000194508,0.0000345069,0.000456176,0.00008391356,0.0000648121,0.00008200108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001183151,"about_ca_system_score_gemma":0.00004436129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003768968,"about_ca_topic_score_gemma":0.00005424011,"domain_scores_codex":[0.9991866,0.00007109925,0.0001165823,0.0002330766,0.0002083562,0.0001842869],"domain_scores_gemma":[0.9993988,0.0000265765,0.00004150263,0.0003881542,0.00007344129,0.00007153799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001961121,0.0003082089,0.001501155,0.00004183017,0.0001156752,0.0004396724,0.01937619,0.0001099087,0.01276948,0.3545745,0.005450831,0.6051164],"study_design_scores_gemma":[0.003626586,0.001370834,0.08104004,0.0001020734,0.00006536497,0.0002654954,0.00004839339,0.3604536,0.4123716,0.1319036,0.007242468,0.001509998],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001030474,0.000005700454,0.9448607,0.0002814237,0.0002120315,0.00006823432,2.573086e-7,0.0001188907,0.05342231],"genre_scores_gemma":[0.1505398,0.00000135533,0.8432136,0.0008119717,0.00009040807,0.000004480726,0.000002161144,0.000009238877,0.005327016],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6036065,"threshold_uncertainty_score":0.25857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02691487819667691,"score_gpt":0.230154826028523,"score_spread":0.2032399478318461,"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."}}