{"id":"W2154446851","doi":"10.1109/pacrim.1995.519554","title":"Optimal determination of regularization parameters and the stabilizing operator","year":2002,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Tikhonov regularization; Regularization (linguistics); Parameterized complexity; Image restoration; Operator (biology); Mathematics; Computer science; Smoothness; Mathematical optimization; Algorithm; Computer vision; Artificial intelligence; Inverse problem; Image (mathematics); Image processing; Mathematical analysis","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":[0.0005082985,0.00004378631,0.00007644905,0.00003486589,0.00006509769,0.0000999122,0.0001753119,0.00001958516,0.000009716402],"category_scores_gemma":[0.0001141384,0.00002719415,0.00002025593,0.0001454867,0.00007976255,0.0003267471,0.0000606739,0.00003240891,0.000001485483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005339328,"about_ca_system_score_gemma":0.000004402767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007013546,"about_ca_topic_score_gemma":3.304441e-7,"domain_scores_codex":[0.9994211,0.0001648227,0.0001210705,0.0001149923,0.000109359,0.00006869179],"domain_scores_gemma":[0.9995192,0.0001885714,0.00004015319,0.0001823101,0.0000532997,0.00001650039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003596931,0.00005969312,0.0001751921,0.00003341326,0.00001437037,0.000005832622,0.008055576,0.0007186848,0.02896489,0.1644845,0.0001552621,0.7972966],"study_design_scores_gemma":[0.0006756916,0.00003528532,0.0001277778,0.000006837154,0.000005007651,0.000009350473,0.00003430146,0.9496375,0.04754191,0.001827226,0.00004484316,0.00005430836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04277193,0.00009528885,0.9552854,0.0004589893,0.00004652358,0.00008451554,9.874458e-8,0.00002126321,0.001236047],"genre_scores_gemma":[0.4581388,0.00001029196,0.5414076,0.0001327502,0.000004960818,0.00000243204,1.065158e-7,0.000001883007,0.00030111],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9489188,"threshold_uncertainty_score":0.1108945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02560178076742305,"score_gpt":0.2533985121771064,"score_spread":0.2277967314096833,"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."}}