{"id":"W4364320730","doi":"10.1109/tgrs.2023.3265657","title":"Multilayer Perceptron and Bayesian Neural Network-Based Elastic Implicit Full Waveform Inversion","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; China Scholarship Council; China Postdoctoral Science Foundation","keywords":"Artificial neural network; Computer science; Inversion (geology); Waveform; Multilayer perceptron; Algorithm; Perceptron; Inverse problem; Bayesian probability; Artificial intelligence; Mathematics; Geology","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":[0.0002567871,0.0001578688,0.0001377634,0.0002298879,0.0008041362,0.00009160861,0.00007664321,0.00007723153,0.00004402094],"category_scores_gemma":[0.000005732004,0.0001268968,0.00004869364,0.0004982582,0.0002578607,0.000225324,0.00000150259,0.000220727,0.00004697667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008861436,"about_ca_system_score_gemma":0.00002845192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003164209,"about_ca_topic_score_gemma":0.0002851113,"domain_scores_codex":[0.9987913,0.00004638922,0.0001503261,0.0003741009,0.0002193571,0.0004185182],"domain_scores_gemma":[0.9995036,0.0001252171,0.00004013241,0.0001426527,0.00002569012,0.0001627447],"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":[0.00003061434,0.000002695288,0.00006626699,0.00001054182,0.000002237877,0.00001079333,0.0001436051,0.008843756,0.0007265522,1.667914e-7,0.0001484016,0.9900144],"study_design_scores_gemma":[0.0001850673,0.0001736343,0.004245236,0.00006590561,0.00001465201,0.00005149185,0.0002322188,0.9929596,0.001354894,0.0001232592,0.0004242561,0.0001697417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.645163,0.00002118305,0.3525502,0.0009918304,0.0005960549,0.0001318974,0.000008062636,0.0002742575,0.0002634934],"genre_scores_gemma":[0.9858855,0.0001213605,0.01234151,0.001387296,0.00004489515,3.243578e-8,0.000005700899,0.000005466462,0.0002082052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9898446,"threshold_uncertainty_score":0.6184847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01407783898177224,"score_gpt":0.2231871314709207,"score_spread":0.2091092924891484,"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."}}