{"id":"W2331013585","doi":"10.1190/segam2015-5924937.1","title":"Time compressively sampled full-waveform inversion with stochastic optimization","year":2015,"lang":"en","type":"article","venue":"","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Petrobras; BG Group; ConocoPhillips","keywords":"Inversion (geology); Computer science; Waveform; Algorithm; Time domain; Seismic migration; Mathematical optimization; Geology; Mathematics; Geophysics; Telecommunications; Computer vision; Seismology","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":[0.0004083782,0.0003920138,0.0003580642,0.0001517693,0.0001713121,0.000446807,0.0004957902,0.0004617229,0.001585274],"category_scores_gemma":[0.001272085,0.0002329472,0.0002920342,0.0002705256,0.0003987344,0.0006188541,0.0005846479,0.0007050604,0.0004440158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000294099,"about_ca_system_score_gemma":0.0008201778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003167951,"about_ca_topic_score_gemma":0.003802281,"domain_scores_codex":[0.9998273,0.00004574662,0.000007548844,0.00002390604,0.00008318428,0.00001230005],"domain_scores_gemma":[0.9995952,0.0001917589,0.00004722437,0.00006322393,0.00008122024,0.00002137249],"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":[0.00009146524,0.00003396909,0.0003345991,0.00005366851,0.00001995304,0.00004033925,0.00003536787,0.9312668,0.0129095,0.01259866,0.00141381,0.04120174],"study_design_scores_gemma":[0.000003149361,0.000005466138,0.00002479694,0.000001019243,5.928534e-7,0.000003901681,0.00000146278,0.9977608,0.0008624126,0.001090597,0.000243978,0.000001808866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01399123,0.00004852365,0.9839391,0.0001317017,0.00002298243,0.00001941215,0.00007658599,0.0003716654,0.001398821],"genre_scores_gemma":[0.3842037,0.0001210701,0.6115276,0.000110381,0.00005194988,0.000108846,0.0005327326,0.0001809321,0.003162748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003167951,"threshold_uncertainty_score":0.006299019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02195987740441054,"score_gpt":0.2038179308552552,"score_spread":0.1818580534508447,"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."}}