{"id":"W2120792566","doi":"10.1016/j.amc.2006.05.052","title":"A fast deblurring algorithm","year":2006,"lang":"en","type":"article","venue":"Applied Mathematics and Computation","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Deblurring; Algorithm; Truncation (statistics); Heat equation; Simple (philosophy); Mathematics; Operator (biology); Computer science; Image (mathematics); Image restoration; Applied mathematics; Image processing; Computer vision; 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":[0.0002069976,0.00008538026,0.0001089362,0.00005667486,0.0001048884,0.0001986141,0.0001238388,0.00002792509,0.000001049327],"category_scores_gemma":[0.000002797022,0.00007887303,0.00001894475,0.0001410307,0.00001736123,0.0001027394,0.00007392427,0.00004758534,0.0000140754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008977946,"about_ca_system_score_gemma":0.000009514773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009476929,"about_ca_topic_score_gemma":3.560696e-7,"domain_scores_codex":[0.9993997,0.000007555336,0.0001652249,0.0001671331,0.0001371763,0.0001231688],"domain_scores_gemma":[0.9996774,0.00008893324,0.00006453125,0.0001123243,0.00003059695,0.00002621203],"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":[5.931709e-7,0.00004477821,9.992851e-7,0.00002554191,0.000003768181,0.000003841782,0.00036717,0.001048638,0.00371521,0.2985913,0.0001095474,0.6960886],"study_design_scores_gemma":[0.0002401685,0.00001041442,0.00007167232,0.000009313002,0.000004307582,0.00001738925,0.00002405446,0.6781355,0.00268587,0.3186205,0.00008804568,0.00009269445],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004481339,0.00004333018,0.986042,0.00004891275,0.00004524944,0.00009093508,2.81356e-7,0.0001044704,0.009143542],"genre_scores_gemma":[0.1049501,0.00000131483,0.8948783,0.00006652218,0.00004206746,0.000007809171,0.000002282892,0.000006306842,0.00004529989],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6959959,"threshold_uncertainty_score":0.3216349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01347833570367004,"score_gpt":0.2540365018183229,"score_spread":0.2405581661146529,"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."}}