{"id":"W2591032368","doi":"10.1088/1742-2140/aa5af5","title":"McMC-based nonlinear EIVAZ inversion driven by rock physics","year":2017,"lang":"en","type":"article","venue":"Journal of Geophysics and Engineering","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Isotropy; Azimuth; Nonlinear system; Anisotropy; Markov chain Monte Carlo; Transverse isotropy; Inversion (geology); Geology; Monte Carlo method; Physics; Algorithm; Mathematical analysis; Geometry; Mathematics; Optics; Seismology; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.00009030973,0.00009023639,0.0001448485,0.00003439147,0.0001638372,0.0000999075,0.0001916204,0.00003235015,0.00001833801],"category_scores_gemma":[0.00002257756,0.00007560253,0.00006159354,0.0000309769,0.00002044991,0.0003551805,0.00001264677,0.0001699175,0.000008299676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003763234,"about_ca_system_score_gemma":0.00001978156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002167613,"about_ca_topic_score_gemma":4.524638e-7,"domain_scores_codex":[0.9995089,0.000005532382,0.0001314589,0.00007362963,0.0001522909,0.0001282317],"domain_scores_gemma":[0.9995371,0.00002910202,0.0001689116,0.000126016,0.00004896189,0.00008996349],"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":[0.0001690003,0.0001771032,0.2116987,0.0003545248,0.0002509998,0.0001216514,0.000523491,0.1502141,0.03847156,0.0001394521,0.06626355,0.5316159],"study_design_scores_gemma":[0.0003941238,0.0001674265,0.01681013,0.0001066123,0.00002350995,0.000008700247,0.00002343703,0.9534699,0.006092347,0.000253598,0.02248002,0.0001701658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978371,0.0002988774,0.01965871,0.0006729509,0.0004879154,0.00004186361,0.00002454364,0.00003247206,0.0004117136],"genre_scores_gemma":[0.9948413,0.0001152199,0.004514587,0.0002183485,0.0002620447,5.393277e-8,0.000007056768,0.000004204725,0.00003718148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8032559,"threshold_uncertainty_score":0.3082981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00767593220132442,"score_gpt":0.188949181601325,"score_spread":0.1812732494000006,"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."}}