{"id":"W2888504409","doi":"10.1190/geo2017-0824.1","title":"Uncertainty quantification for inverse problems with weak partial-differential-equation constraints","year":2018,"lang":"en","type":"article","venue":"Geophysics","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Posterior probability; Uncertainty quantification; Inverse problem; Applied mathematics; Mathematics; Markov chain Monte Carlo; Mathematical optimization; Covariance; Gaussian; Bayesian probability; Partial differential equation; Prior probability; Computer science; Algorithm; Statistics; Mathematical analysis","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":[0.004746364,0.001108885,0.001000205,0.001693134,0.0006110595,0.001772897,0.001228988,0.001344638,0.001647923],"category_scores_gemma":[0.01271322,0.000650208,0.001159961,0.0009780239,0.002475345,0.002390976,0.003370429,0.001985462,0.0002245739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001168412,"about_ca_system_score_gemma":0.001183152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00293593,"about_ca_topic_score_gemma":0.001498002,"domain_scores_codex":[0.9978502,0.0008123728,0.0001320628,0.0002408914,0.0008418561,0.00012273],"domain_scores_gemma":[0.9913914,0.006749241,0.0004969973,0.0003023476,0.0008655785,0.0001944629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003077188,0.00002855732,0.0006189132,0.0001388545,0.00003574206,0.000120413,0.0001259711,0.7512439,0.00332288,0.2279562,0.0006239908,0.01575374],"study_design_scores_gemma":[0.000002753284,0.000006750408,0.00008599042,0.00001396072,0.000003086992,0.00001434406,0.000009318753,0.9479728,0.0006846845,0.05047587,0.0007210093,0.000009598236],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003996285,0.0001145126,0.9946346,0.0001285016,0.00001756471,0.00001674316,0.00003765358,0.0000384902,0.001015638],"genre_scores_gemma":[0.4911213,0.0008447092,0.5032406,0.00032725,0.0001978517,0.0002730392,0.0003407559,0.0002293022,0.003425326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004746364,"threshold_uncertainty_score":0.02510148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03330699774230627,"score_gpt":0.2323359891639741,"score_spread":0.1990289914216678,"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."}}