{"id":"W4410317096","doi":"10.1038/s41598-025-96859-x","title":"Rapid eigenpatch utility classifier for image denoising","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Laidlaw Foundation; Irish Research Council; Science Foundation Ireland","keywords":"Computer science; Artificial intelligence; Noise reduction; Convolutional neural network; Pattern recognition (psychology); USable; Smoothing; Classifier (UML); Image restoration; Image (mathematics); Computer vision; Image processing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001502294,0.0006499912,0.0006796576,0.001143983,0.0003481507,0.0008376741,0.001194422,0.000926053,0.002187474],"category_scores_gemma":[0.003339722,0.0002649454,0.0005282963,0.000807407,0.0004807903,0.0009890731,0.0008419766,0.001089172,0.001067268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006806971,"about_ca_system_score_gemma":0.0009150909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002597071,"about_ca_topic_score_gemma":0.004272265,"domain_scores_codex":[0.9993182,0.00009500032,0.00004012195,0.0001451574,0.0003272319,0.00007426542],"domain_scores_gemma":[0.9989156,0.0002826728,0.0001044204,0.0001915752,0.0004583683,0.00004748915],"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":[0.0003371105,0.0001599173,0.002092851,0.0001151288,0.00008658556,0.0001599542,0.00009585227,0.09902963,0.09005471,0.01019939,0.008543032,0.7891259],"study_design_scores_gemma":[0.000005239433,0.00005126075,0.0006842371,0.000008130717,0.00001088513,0.0001144195,0.00001509403,0.9651698,0.02925007,0.002455109,0.002223541,0.00001217828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01746821,0.0002667476,0.9793373,0.0001056543,0.00004841353,0.00005634984,0.00008007736,0.001500333,0.001136801],"genre_scores_gemma":[0.3795719,0.0004427975,0.6094105,0.0002538659,0.00007921799,0.0001494374,0.0007445802,0.000293011,0.009054816],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002597071,"threshold_uncertainty_score":0.007944942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03494179622866834,"score_gpt":0.3144231239745037,"score_spread":0.2794813277458354,"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."}}