{"id":"W2945262583","doi":"10.1190/geo2018-0619.1","title":"Least-squares reverse time migration via linearized waveform inversion using a Wasserstein metric","year":2019,"lang":"en","type":"article","venue":"Geophysics","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities","keywords":"Mathematics; Norm (philosophy); Metric (unit); Seismogram; Algorithm; Applied mathematics; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001864846,0.0001468837,0.0001877421,0.0001767832,0.0001289988,0.00005231305,0.0001654966,0.00007978029,0.0009780501],"category_scores_gemma":[0.00001931852,0.0001266565,0.00009720703,0.0005577505,0.00003780767,0.0005019347,0.00001983317,0.0001504833,0.003275851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000019324,"about_ca_system_score_gemma":0.00004631379,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0115473,"about_ca_topic_score_gemma":0.0000183441,"domain_scores_codex":[0.9989802,0.00005256249,0.000171996,0.0002502607,0.0002911006,0.0002539329],"domain_scores_gemma":[0.9994534,0.00004977889,0.0001110797,0.0002446024,0.0000650203,0.00007615204],"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":[0.0006611153,0.0002476667,0.1566594,0.0003739655,0.0002109945,0.00004565546,0.002407573,0.009697447,0.09554644,0.0000906223,0.07313859,0.6609205],"study_design_scores_gemma":[0.000370076,0.0001633812,0.002231701,0.0000392135,0.00003044886,0.000005391606,0.0001704944,0.9743967,0.008264454,0.0008829838,0.01319089,0.0002542663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950462,0.00006567097,0.001363033,0.0002385589,0.0003803249,0.0002254246,0.00002067552,0.0001647519,0.002495381],"genre_scores_gemma":[0.9920082,0.00002273204,0.004202321,0.001115901,0.0001211058,3.707603e-7,0.0002084155,0.000006998245,0.002313951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9646993,"threshold_uncertainty_score":0.9999352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009544473786315387,"score_gpt":0.1970467683117415,"score_spread":0.1875022945254261,"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."}}