{"id":"W2206363546","doi":"10.1190/geo2014-0374.1","title":"Bayesian inversion of pressure diffusivity from microseismicity","year":2015,"lang":"en","type":"article","venue":"Geophysics","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Division of Mathematical Sciences; National Science Foundation","keywords":"Microseism; Geology; Hydraulic fracturing; Inversion (geology); Probabilistic logic; Fluid dynamics; Fluid pressure; Uncertainty quantification; Seismology; Petroleum engineering; Computer science; Mechanics; Machine learning; Tectonics","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":[0.00004449028,0.00009868586,0.0001856605,0.00002771704,0.00002150299,0.00001015218,0.0001368756,0.00006958462,0.00001594438],"category_scores_gemma":[0.0000129382,0.00009018091,0.00007946252,0.000121207,0.00002917641,0.00007518333,0.00004535112,0.0001210988,0.00003528269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001754502,"about_ca_system_score_gemma":0.00001316852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001400227,"about_ca_topic_score_gemma":0.00002111826,"domain_scores_codex":[0.9994714,0.00001883483,0.0001140426,0.0001081314,0.0001555927,0.0001319894],"domain_scores_gemma":[0.9995462,0.00002276173,0.00002891805,0.0002683604,0.00003899605,0.00009475091],"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":[0.00002153644,0.000132836,0.004435459,0.0001540939,0.0004198354,0.000007552262,0.002004582,0.9426888,0.02957483,0.00001439934,0.01391001,0.006636013],"study_design_scores_gemma":[0.000758256,0.00003467214,0.009180651,0.00005262705,0.0002309171,4.435514e-7,0.0001425277,0.8505647,0.1116838,0.00452758,0.02244203,0.0003818745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810406,0.0002735569,0.01668503,0.00005017972,0.000183284,0.00003971288,0.0000473292,0.0001088641,0.001571469],"genre_scores_gemma":[0.9992785,0.00001646753,0.0003228625,0.00002685827,0.000128388,0.000001209341,0.00002846379,0.00001396494,0.0001833051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09212422,"threshold_uncertainty_score":0.3677471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008070054617823876,"score_gpt":0.1927835577497867,"score_spread":0.1847135031319628,"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."}}