{"id":"W2033097986","doi":"10.1016/j.ins.2014.02.018","title":"Analysis and extension of multiresolution singular value decomposition","year":2014,"lang":"en","type":"article","venue":"Information Sciences","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Winnipeg; University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Extension (predicate logic); Singular value decomposition; Decomposition; Multiresolution analysis; Value (mathematics); Mathematics; Singular spectrum analysis; Pure mathematics; Computer science; Statistics; Algorithm; Artificial intelligence; Wavelet","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009887462,0.0004768892,0.0005574732,0.001376557,0.0002243515,0.0009540683,0.0005292941,0.0004987443,0.001733654],"category_scores_gemma":[0.003308942,0.0002534334,0.0008477802,0.001006356,0.0005312025,0.001379353,0.0008315092,0.001013635,0.0004431838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001965751,"about_ca_system_score_gemma":0.0003642848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005476552,"about_ca_topic_score_gemma":0.0005052066,"domain_scores_codex":[0.9995856,0.00009764179,0.00002647294,0.00009478137,0.0001657553,0.00002976648],"domain_scores_gemma":[0.998852,0.0003154385,0.0001548183,0.0002770569,0.0003494374,0.00005124095],"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":[0.0002233909,0.0001484879,0.001941188,0.0005270462,0.0001709234,0.0005064176,0.0003860703,0.08351693,0.09235724,0.2880421,0.003687655,0.5284926],"study_design_scores_gemma":[0.00001006858,0.00006980247,0.002675612,0.00004082351,0.00007268041,0.0004465776,0.00006060433,0.8890786,0.009626795,0.08927204,0.008612459,0.00003385424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.017124,0.001176169,0.9791393,0.0001576465,0.0001116324,0.00001404824,0.00005967324,0.0001207902,0.002096819],"genre_scores_gemma":[0.485506,0.005238491,0.4988934,0.0001742643,0.0006603352,0.00005342853,0.0004240884,0.0001963183,0.008853668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001733654,"threshold_uncertainty_score":0.005799651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01782861362058961,"score_gpt":0.3102062427374182,"score_spread":0.2923776291168286,"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."}}