{"id":"W2897326031","doi":"10.1139/cgj-2018-0409","title":"Bayesian updating of subsurface spatial variability for improved prediction of braced excavation response","year":2018,"lang":"en","type":"article","venue":"Canadian Geotechnical Journal","topic":"Geotechnical Engineering and Analysis","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inclinometer; Bayesian probability; Computer science; Field (mathematics); Deflection (physics); Process (computing); Engineering; Data mining; Geology; Artificial intelligence; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001626547,0.0001352532,0.0002875632,0.0002662373,0.00009347971,0.00001848006,0.0002080369,0.000241252,0.00007492436],"category_scores_gemma":[0.001391653,0.000140509,0.00015832,0.0003577757,0.00009716828,0.00009419437,0.00001285545,0.0003304048,0.000001083119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002223112,"about_ca_system_score_gemma":0.0002508366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001915389,"about_ca_topic_score_gemma":0.0006036283,"domain_scores_codex":[0.9986879,0.00006270043,0.0006409839,0.0001495276,0.0001349651,0.0003239034],"domain_scores_gemma":[0.9987833,0.0001951288,0.0001237147,0.0002699158,0.0003039513,0.0003239636],"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":[0.0002203063,0.00003292352,0.0002151869,0.00009561421,0.0001432366,0.000002043096,0.00007045804,0.6176689,0.361816,0.0001834642,0.0006992813,0.01885265],"study_design_scores_gemma":[0.0003664995,0.0002396906,0.004190152,0.00006159143,0.000056182,0.00001646167,0.00001795188,0.9776406,0.01496903,0.0004644183,0.001852194,0.0001252283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.110313,0.00002069635,0.8887301,0.0002621291,0.0002213837,0.000172133,0.0001413704,0.00009572035,0.00004346108],"genre_scores_gemma":[0.9941887,0.000007127089,0.005553354,0.00001542056,0.000177761,0.000006704271,0.00001228304,0.00002637694,0.00001231839],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8838757,"threshold_uncertainty_score":0.572979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006418201803574435,"score_gpt":0.2004930457820794,"score_spread":0.1940748439785049,"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."}}