{"id":"W2013880577","doi":"10.1115/ipc2002-27224","title":"Probability of Exceedance (POE) Methodology for Developing Integrity Programs Based on Pipeline Operator-Specific Technical and Economic Factors","year":2002,"lang":"en","type":"article","venue":"4th International Pipeline Conference, Parts A and B","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"TransCanada (Canada)","funders":"","keywords":"Pipeline (software); Integrity management; Reliability engineering; Schedule; Interval (graph theory); Process (computing); Probabilistic logic; Computer science; Pipeline transport; Risk analysis (engineering); Scope (computer science); Engineering; Operations research; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004090963,0.0002256831,0.0004230602,0.0001269945,0.00006154885,0.00006438226,0.0001932765,0.0001835286,0.0001867568],"category_scores_gemma":[0.0002283866,0.0001754374,0.0001033321,0.00007686253,0.0002532798,0.0001099852,0.00004036734,0.0002986052,0.000002518278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008535682,"about_ca_system_score_gemma":0.00002778074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000680239,"about_ca_topic_score_gemma":0.0002410475,"domain_scores_codex":[0.9987139,0.00006009431,0.0005346181,0.0003712259,0.0001281667,0.0001919555],"domain_scores_gemma":[0.9990645,0.0003673132,0.00008214077,0.0001692789,0.0002424261,0.0000743381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009986493,0.001258667,0.1556133,0.002258685,0.0008246624,0.00001113782,0.002540115,0.0281961,0.01479853,0.3662023,0.01132238,0.4159755],"study_design_scores_gemma":[0.0009365026,0.0002029552,0.00747631,0.0001868799,0.00004976999,0.000009449124,0.0001337404,0.9501241,0.007679188,0.008272086,0.02446458,0.00046437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8477079,0.0002780863,0.1470404,0.001938687,0.0006809225,0.000625924,0.0001459047,0.0001399264,0.001442286],"genre_scores_gemma":[0.9799216,0.0002356501,0.01945408,0.0000529659,0.0001119515,0.00004893967,0.00006258459,0.00001211373,0.0001000726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.921928,"threshold_uncertainty_score":0.715413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1592720969744279,"score_gpt":0.306098027290948,"score_spread":0.1468259303165201,"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."}}