{"id":"W3095647047","doi":"10.1016/j.jngse.2020.103698","title":"Reliability evaluation method for pipes buried in fault areas based on the probabilistic fault displacement hazard analysis","year":2020,"lang":"en","type":"article","venue":"Journal of Natural Gas Science and Engineering","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Chinese Government Scholarship; National Natural Science Foundation of China","keywords":"Displacement (psychology); Conditional probability; Fault (geology); Structural engineering; Engineering; Probabilistic logic; Monte Carlo method; Reliability (semiconductor); Fault tree analysis; Seismic hazard; Reliability engineering; Geology; Seismology; Statistics; Mathematics","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":[0.0007942133,0.0005446307,0.000612681,0.001386012,0.0003383836,0.0004747649,0.0006508649,0.0004410691,0.001279728],"category_scores_gemma":[0.002206219,0.0003040388,0.0005690383,0.0004947204,0.000248893,0.0006537296,0.0003168861,0.0003161212,0.0001585006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004942547,"about_ca_system_score_gemma":0.0006209958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002529703,"about_ca_topic_score_gemma":0.002152723,"domain_scores_codex":[0.9994815,0.0001400111,0.00003700388,0.00008503952,0.0002241237,0.00003229639],"domain_scores_gemma":[0.9988053,0.000520997,0.0001132804,0.00005725386,0.0004713396,0.00003190048],"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":[0.000255214,0.00008094299,0.008813101,0.0003789178,0.0001375568,0.0002217752,0.0002331664,0.6881602,0.02816741,0.00806525,0.001398792,0.2640876],"study_design_scores_gemma":[0.000005563547,0.00004793021,0.001411604,0.000008831184,0.00002676579,0.00006843831,0.00001747503,0.9956104,0.001484934,0.001033267,0.0002739539,0.0000108738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06278901,0.0004687555,0.9351832,0.00007594867,0.0000244882,0.00004695167,0.00005878381,0.0002764711,0.001076425],"genre_scores_gemma":[0.9123038,0.0002579104,0.08615396,0.00001736575,0.00003065598,0.00006741264,0.0001221644,0.0000297942,0.001016821],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002529703,"threshold_uncertainty_score":0.005029917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01435880762609734,"score_gpt":0.2658903806099757,"score_spread":0.2515315729838783,"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."}}