{"id":"W2334735746","doi":"10.1190/segam2012-1552.1","title":"Imaging with multiples accelerated by message passing","year":2012,"lang":"en","type":"article","venue":"","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Multiple; Solver; Inversion (geology); Computer science; Algorithm; Least-squares function approximation; Operator (biology); Mathematical optimization; Geology; Mathematics; Seismology; Arithmetic; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00141585,0.001130455,0.001038194,0.0006707358,0.0006531445,0.001391397,0.001528939,0.001246631,0.00459454],"category_scores_gemma":[0.003861378,0.0004530076,0.0007105616,0.0008135212,0.001084953,0.001900388,0.001707669,0.001977089,0.001718658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009214024,"about_ca_system_score_gemma":0.001361075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00411841,"about_ca_topic_score_gemma":0.004523037,"domain_scores_codex":[0.9989912,0.0002569849,0.00004525462,0.0001371033,0.0004601653,0.0001093143],"domain_scores_gemma":[0.9980799,0.0008855729,0.0001536933,0.000427565,0.0003749063,0.00007829394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005465478,0.0001454021,0.000821794,0.0001957937,0.00008110893,0.0002635731,0.000458496,0.6503181,0.02703504,0.09948474,0.005588441,0.2150609],"study_design_scores_gemma":[0.00002385653,0.0000258056,0.00002379873,0.000004847276,0.000005071576,0.00002079042,0.00001135096,0.9851928,0.003585639,0.008830595,0.002268934,0.000006647516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00868469,0.0001246302,0.9876632,0.0002249183,0.00006188493,0.00003352754,0.00002709737,0.001688869,0.001491142],"genre_scores_gemma":[0.227885,0.0002217011,0.7646386,0.0001272115,0.00009794941,0.0002651429,0.0001628122,0.0002146976,0.00638685],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00459454,"threshold_uncertainty_score":0.01537025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01843933592258601,"score_gpt":0.2199196227536196,"score_spread":0.2014802868310336,"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."}}