{"id":"W2331201205","doi":"10.1190/segam2013-1313.1","title":"Separation of simultaneous source data via iterative rank reduction","year":2013,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Reduction (mathematics); Computer science; Rank (graph theory); Iterative method; Data reduction; Algorithm; Data mining; Mathematics","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":[0.00008647473,0.00006018478,0.00007674136,0.00003976033,0.00006002388,0.0001291278,0.0004981986,0.00002663946,0.00006281502],"category_scores_gemma":[0.00004126311,0.00004880278,0.00001195971,0.0001846882,0.00002344424,0.001437185,0.0001541731,0.00004317631,0.00009421126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001052294,"about_ca_system_score_gemma":0.00002721789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004670803,"about_ca_topic_score_gemma":0.000002493355,"domain_scores_codex":[0.9993598,0.00002377191,0.00014368,0.0002367464,0.000134344,0.0001016656],"domain_scores_gemma":[0.9992436,0.00005200395,0.00007948252,0.0004693607,0.0001228445,0.0000326936],"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":[0.000004158312,0.00004651944,0.00003733422,0.00001355978,0.00001193625,0.000001301794,0.001163489,0.001677897,0.2975754,0.0001590433,0.003803948,0.6955054],"study_design_scores_gemma":[0.0001168867,0.00003719986,0.00002570449,0.000009226799,0.000002303149,0.00002408481,0.00005244013,0.5583834,0.4395344,0.0009945035,0.0007423213,0.00007750707],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05397631,0.00004262461,0.9433613,0.0004219495,0.0001003993,0.0000999849,5.266904e-7,0.00008119852,0.001915648],"genre_scores_gemma":[0.866646,0.000002227297,0.1317668,0.00008131379,0.00005293666,0.000002442599,0.000009043079,0.000002691344,0.001436595],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8126697,"threshold_uncertainty_score":0.199012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02035539757862916,"score_gpt":0.2829273186714848,"score_spread":0.2625719210928557,"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."}}