{"id":"W4413120623","doi":"10.1109/access.2025.3597217","title":"Image Coding With Data-Driven Fast Transforms Based on Approximate Givens Factorizations","year":2025,"lang":"en","type":"article","venue":"IEEE Access","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Coding (social sciences); Theoretical computer science; Algorithm; Computer graphics (images); Computer vision; Parallel computing; Artificial intelligence; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002874509,0.000164329,0.0001873732,0.0002081382,0.0002575054,0.0008209695,0.002325841,0.00004598423,0.00001381041],"category_scores_gemma":[0.00002777191,0.0001238604,0.00003560307,0.0008155976,0.00005837088,0.001726718,0.000137033,0.0001669517,0.000009198442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003531904,"about_ca_system_score_gemma":0.0001495268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002900897,"about_ca_topic_score_gemma":0.0000126358,"domain_scores_codex":[0.9986682,0.00009246809,0.0002026,0.0004980508,0.0002666338,0.0002720372],"domain_scores_gemma":[0.9985606,0.0001728012,0.00006433847,0.001036865,0.0001057766,0.00005959422],"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":[0.001029872,0.002691067,0.008292779,0.001612486,0.0007455085,0.001160453,0.005808207,0.1218362,0.1919939,0.06523065,0.06628571,0.5333132],"study_design_scores_gemma":[0.001084883,0.00007003997,0.0008349641,0.000142791,0.00002957077,0.000002869505,0.00001326159,0.9575521,0.03668619,0.001030126,0.002277012,0.0002762098],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007402223,0.000005332307,0.987829,0.0009149486,0.0004103258,0.0002202361,0.0000419112,0.000188581,0.009649462],"genre_scores_gemma":[0.6992103,0.000006206511,0.2981268,0.002079012,0.00008062123,0.00002718578,0.00007620094,0.00002232001,0.0003714086],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8357159,"threshold_uncertainty_score":0.7916628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04949538373396389,"score_gpt":0.3407871918671357,"score_spread":0.2912918081331718,"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."}}