{"id":"W2166607166","doi":"10.1109/joe.2010.2100490","title":"Bayesian Inversion of Interface-Wave Dispersion for Seabed Shear-Wave Speed Profiles","year":2011,"lang":"en","type":"article","venue":"IEEE Journal of Oceanic Engineering","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Covariance; Power law; Covariance matrix; Gaussian; Mathematics; Bayesian probability; Probability distribution; Geology; Algorithm; Statistics; Physics","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":[0.0004866977,0.0001279103,0.0002458779,0.0002591213,0.00003753532,0.00002096038,0.0001936374,0.00007198915,0.0003803145],"category_scores_gemma":[0.00008267623,0.0001016918,0.0001228077,0.000143885,0.00003456329,0.0002667876,0.00001377461,0.000243539,0.000007030296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002234773,"about_ca_system_score_gemma":0.00006360353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003680687,"about_ca_topic_score_gemma":0.000004660629,"domain_scores_codex":[0.9988329,0.00002503935,0.0003917635,0.0001145882,0.0003475918,0.0002881469],"domain_scores_gemma":[0.9992647,0.00012831,0.0001559208,0.0001126086,0.0001617073,0.0001767354],"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":[0.001910112,0.0002519597,0.03325513,0.001755356,0.0006871555,0.0003416612,0.006981259,0.4776294,0.4570157,0.0000229098,0.003915305,0.01623406],"study_design_scores_gemma":[0.0005350888,0.0006399023,0.006174427,0.0001880365,0.00003453558,0.00009070617,0.0001959952,0.8428608,0.1489931,0.00009063049,0.00006902539,0.0001278524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.70597,0.0001902644,0.2924925,0.00003870414,0.0007073221,0.0002089985,0.00003012138,0.00001493745,0.0003470876],"genre_scores_gemma":[0.977544,0.00006110274,0.02215989,0.000006601568,0.0001520372,8.499881e-8,0.000003391507,0.00000975459,0.00006316421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3652313,"threshold_uncertainty_score":0.4164177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04893566774290115,"score_gpt":0.2366881311905648,"score_spread":0.1877524634476637,"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."}}