{"id":"W2432841566","doi":"10.1016/j.ijpvp.2016.06.003","title":"Statistical analyses of incidents on onshore gas transmission pipelines based on PHMSA database","year":2016,"lang":"en","type":"article","venue":"International Journal of Pressure Vessels and Piping","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":196,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Pipeline and Hazardous Materials Safety Administration","keywords":"Pipeline transport; Corrosion; Pipeline (software); Hazardous waste; Forensic engineering; Environmental science; Statistical analysis; Engineering; Petroleum engineering; Waste management; Materials science; Environmental engineering; Metallurgy; 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":[0.003689951,0.0003090733,0.0005522636,0.004054865,0.0003945335,0.001056002,0.0007499272,0.0003606679,0.003796702],"category_scores_gemma":[0.01486655,0.000216433,0.0009441791,0.004719675,0.0003279152,0.0007486259,0.0006922187,0.0007122318,0.0004551545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005510962,"about_ca_system_score_gemma":0.0013608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008028808,"about_ca_topic_score_gemma":0.005947902,"domain_scores_codex":[0.9941316,0.001320366,0.001299485,0.001247306,0.001513891,0.0004873586],"domain_scores_gemma":[0.9706303,0.01654621,0.00701432,0.001899969,0.003165569,0.000743717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006014099,0.0001218063,0.9837266,0.0001181948,0.000525675,0.0001692738,0.0001591661,0.002139909,0.0004510849,0.0002397589,0.00214589,0.009601254],"study_design_scores_gemma":[0.00002509057,0.0002759517,0.9877554,0.00003478276,0.0002296448,0.0002862908,0.0009618907,0.007124223,0.0007154449,0.0001939142,0.002379379,0.00001815779],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.940066,0.0001483849,0.002595908,0.00009343991,0.00002307843,0.0001465141,0.05552017,0.0001201161,0.001286366],"genre_scores_gemma":[0.9538571,0.0001218929,0.002222648,0.00002965124,0.00002919725,0.0002710003,0.04292912,0.00002638116,0.0005129183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008028808,"threshold_uncertainty_score":0.0195145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02932322748749447,"score_gpt":0.3226778272383416,"score_spread":0.2933545997508471,"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."}}