{"id":"W2512268460","doi":"10.1190/segam2016-13878249.1","title":"Time-jittered marine acquisition: A rank-minimization approach for 5D source separation","year":2016,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; SENAI CIMATEC; BG Group","keywords":"Minification; Computer science; Rank (graph theory); Algorithm; Mathematics; Combinatorics; World Wide Web","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":[0.0004298636,0.0001449463,0.0001521312,0.0001370619,0.0001172364,0.0001618386,0.0004204057,0.0001034483,0.0001805822],"category_scores_gemma":[0.00003823819,0.0001039036,0.00007737538,0.0002515682,0.00003770699,0.000929471,0.0001496415,0.00003681932,0.00009599568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004748051,"about_ca_system_score_gemma":0.00004387551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003062976,"about_ca_topic_score_gemma":9.332272e-7,"domain_scores_codex":[0.9987732,0.0001054089,0.0002821657,0.0004168165,0.0002199165,0.0002025475],"domain_scores_gemma":[0.99901,0.0001303282,0.0001236937,0.000481619,0.0001891529,0.00006525375],"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":[0.0003067176,0.000743421,0.0005389205,0.00008496694,0.0001208525,0.000001817589,0.003355592,0.001977104,0.04840431,0.3565489,0.1815343,0.4063831],"study_design_scores_gemma":[0.002432622,0.0003830757,0.000648414,0.00002229522,0.00001768,0.00002576217,0.00002501982,0.8796834,0.06327173,0.01402549,0.03884507,0.0006194735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001041009,0.000004636145,0.9831105,0.003109564,0.00004329661,0.0006129559,0.000002959512,0.0009135398,0.01116148],"genre_scores_gemma":[0.1809406,0.000005855508,0.7938674,0.002103495,0.000149768,0.0002773703,0.00008667384,0.00002286974,0.02254594],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8777062,"threshold_uncertainty_score":0.4237068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01879560533362648,"score_gpt":0.2622892988837976,"score_spread":0.2434936935501711,"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."}}