{"id":"W3090206325","doi":"10.1190/segam2020-3425671.1","title":"Iterative deblending with robust Fourier thresholding","year":2020,"lang":"en","type":"article","venue":"","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Fourier transform; Computer science; Algorithm; Robustness (evolution); Thresholding; Iterative method; White noise; Gaussian; Computer vision; Mathematics; Telecommunications; Image (mathematics); Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001912123,0.001154594,0.001106321,0.0009768142,0.0005793966,0.001774579,0.001549035,0.001772681,0.003673291],"category_scores_gemma":[0.006727188,0.0005426632,0.00116766,0.001218369,0.001505926,0.00216368,0.002752609,0.002127586,0.001410647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007618164,"about_ca_system_score_gemma":0.001128016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001806415,"about_ca_topic_score_gemma":0.002578074,"domain_scores_codex":[0.9988145,0.0002718979,0.00007382642,0.0002787737,0.0004787925,0.00008233167],"domain_scores_gemma":[0.9985541,0.0005698208,0.0001341636,0.0004235716,0.0002621327,0.0000562606],"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":[0.0004071209,0.0001126684,0.001122784,0.0003593809,0.0001415734,0.0002861138,0.0006425372,0.3627536,0.06172648,0.1463612,0.008004775,0.4180817],"study_design_scores_gemma":[0.00001988695,0.00004239063,0.0002197988,0.00002635794,0.00001174804,0.0001451751,0.00004492437,0.9460096,0.01893865,0.02881697,0.005690097,0.00003428494],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003568429,0.0001082445,0.9943251,0.0001135858,0.00003883582,0.00002983939,0.00003761585,0.0002362363,0.001542181],"genre_scores_gemma":[0.06721198,0.0002240141,0.9270878,0.0001437062,0.00006849875,0.0001061801,0.0002415895,0.0002544273,0.004661718],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003673291,"threshold_uncertainty_score":0.01228839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03289937269733417,"score_gpt":0.1964693725341975,"score_spread":0.1635699998368633,"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."}}