{"id":"W4308884436","doi":"10.1139/cgj-2022-0356","title":"Quantifying reliability of liquefaction severity map developed from sparse cone penetration tests","year":2022,"lang":"en","type":"article","venue":"Canadian Geotechnical Journal","topic":"Geotechnical Engineering and Soil Mechanics","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Liquefaction; Cone penetration test; Penetration test; Geotechnical engineering; Geostatistics; Reliability (semiconductor); Parametric statistics; Spatial variability; Kriging; Geology; Environmental science; Statistics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001108338,0.000844999,0.0004458321,0.002846812,0.0001608303,0.0007352599,0.0005973806,0.0005887962,0.0007933532],"category_scores_gemma":[0.004603712,0.0002153739,0.0003542922,0.001295091,0.0003817194,0.0008554555,0.000723808,0.000397007,0.0002966732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000276565,"about_ca_system_score_gemma":0.0003057142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003471323,"about_ca_topic_score_gemma":0.003049085,"domain_scores_codex":[0.9992297,0.000096245,0.00005585618,0.0001649164,0.0003923605,0.00006092517],"domain_scores_gemma":[0.9964882,0.00116693,0.0007970604,0.0002853643,0.001156005,0.0001064664],"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":[0.0008384942,0.0001359229,0.2037747,0.0008051095,0.0001726249,0.001264969,0.0007061402,0.4327065,0.06692125,0.001801533,0.002404778,0.288468],"study_design_scores_gemma":[0.00001261711,0.0001635722,0.0799416,0.00006015446,0.00005521237,0.0004019566,0.0002824097,0.8887162,0.02804965,0.001165385,0.001068847,0.00008239559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7836437,0.0005696734,0.2105288,0.00009438331,0.00002803188,0.00005535058,0.00129332,0.001062591,0.00272409],"genre_scores_gemma":[0.9856,0.0001815687,0.01307581,0.00001483632,0.00001000756,0.00002622226,0.0006720281,0.00003385499,0.0003857267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003471323,"threshold_uncertainty_score":0.006902218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0243664564859143,"score_gpt":0.2249414378657267,"score_spread":0.2005749813798124,"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."}}