{"id":"W4315482716","doi":"10.1088/1755-1315/1124/1/012075","title":"A Bayesian regression analysis of in situ stress using overcoring data","year":2023,"lang":"en","type":"article","venue":"IOP Conference Series Earth and Environmental Science","topic":"Soil and Unsaturated Flow","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nuclear Waste Management Organization; University of Toronto","funders":"","keywords":"Stress (linguistics); Cauchy stress tensor; Bayesian probability; Regression analysis; Regression; Linear regression; In situ; Principal component analysis; Econometrics; Computer science; Statistics; Data mining; Mathematics; Chemistry; 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":[0.002868327,0.0009629366,0.0006930801,0.002010247,0.0003645579,0.0009790871,0.0006636347,0.0006908269,0.00133314],"category_scores_gemma":[0.006389865,0.0003027701,0.0008007449,0.001960811,0.0004051275,0.0009379444,0.0007344136,0.0007007822,0.0004739382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004865955,"about_ca_system_score_gemma":0.000602821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02038814,"about_ca_topic_score_gemma":0.01959427,"domain_scores_codex":[0.9987238,0.0004210734,0.0000715327,0.0003286295,0.0003377058,0.0001171485],"domain_scores_gemma":[0.9962865,0.00182423,0.0005341323,0.0002949422,0.0009868589,0.00007334493],"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":[0.0004435244,0.0003141336,0.1572125,0.0003832961,0.0004250538,0.0004243945,0.0007959569,0.5616782,0.06594711,0.003597068,0.001491038,0.2072878],"study_design_scores_gemma":[0.00001156781,0.0001121293,0.1290634,0.00003428593,0.00005749396,0.0001228069,0.000211875,0.8603764,0.00677773,0.001587692,0.001549897,0.00009478655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7923175,0.0002906458,0.2032155,0.0001536825,0.00003152991,0.00004931325,0.0009888036,0.0007629119,0.002190102],"genre_scores_gemma":[0.959614,0.0001623665,0.03793382,0.0000188341,0.00002284375,0.00002748496,0.001084997,0.0001625673,0.000973031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02038814,"threshold_uncertainty_score":0.04053891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02620086393854371,"score_gpt":0.2336061595351418,"score_spread":0.2074052955965981,"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."}}