{"id":"W4396785777","doi":"10.1016/j.oceaneng.2024.118086","title":"Time varying reliability analysis of corroded gas pipelines using copula and importance sampling","year":2024,"lang":"en","type":"article","venue":"Ocean Engineering","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Hong Kong Polytechnic University","keywords":"Copula (linguistics); Pipeline transport; Reliability engineering; Reliability (semiconductor); Environmental science; Computer science; Engineering; Forensic engineering; Statistics; Econometrics; Marine engineering; Mathematics; Environmental engineering; Physics","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":[0.00182989,0.0005849344,0.0006474779,0.0010113,0.0002280764,0.0004487447,0.000820455,0.0004571917,0.0006234593],"category_scores_gemma":[0.009754925,0.0004827305,0.000587718,0.0007092002,0.0004230834,0.0007006767,0.0004225246,0.0007390942,0.00008352335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005399063,"about_ca_system_score_gemma":0.000464138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00873715,"about_ca_topic_score_gemma":0.006262396,"domain_scores_codex":[0.9994822,0.0002300591,0.00002611996,0.0000933937,0.0001131681,0.00005511321],"domain_scores_gemma":[0.9942811,0.004165311,0.0005017511,0.000286175,0.0006768361,0.00008893572],"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":[0.00008051675,0.00003181757,0.005389982,0.00003803084,0.00008526418,0.0001306804,0.00005289944,0.9755741,0.002465222,0.003135664,0.0001861897,0.01282958],"study_design_scores_gemma":[7.792182e-7,0.000006531798,0.0008165636,9.093249e-7,0.000003440551,0.000007451789,0.000003646016,0.9987125,0.0001720186,0.0002577073,0.00001677092,0.000001685665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4262991,0.0003152415,0.5723007,0.0001040876,0.00002033417,0.00002693279,0.0001042822,0.0001802409,0.0006491236],"genre_scores_gemma":[0.9824038,0.00009698827,0.01674512,0.000009981696,0.00001513018,0.0000119362,0.0001296666,0.00003506909,0.0005524442],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00873715,"threshold_uncertainty_score":0.01737261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01391746661066759,"score_gpt":0.2389495571465028,"score_spread":0.2250320905358352,"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."}}