{"id":"W2766657842","doi":"10.1115/pvp2017-65289","title":"Statistical Analyses of Incidents on Oil and Gas Pipelines Based on Comparing Different Pipeline Incident Databases","year":2017,"lang":"en","type":"article","venue":"","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Pipeline and Hazardous Materials Safety Administration","keywords":"Pipeline transport; Pipeline (software); Database; Engineering; Fossil fuel; Petroleum engineering; Computer science; Forensic engineering; Waste management; Environmental engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.009993835,0.0003483898,0.0005528281,0.008196712,0.0004022911,0.001162208,0.0006100254,0.0002637226,0.001605716],"category_scores_gemma":[0.04068912,0.0001356496,0.001194987,0.006473992,0.0005965679,0.0009675813,0.0008808051,0.0006816523,0.0002251597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007583285,"about_ca_system_score_gemma":0.0009060058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004822658,"about_ca_topic_score_gemma":0.003385685,"domain_scores_codex":[0.9857289,0.004766661,0.002744505,0.002164492,0.003993932,0.0006014543],"domain_scores_gemma":[0.9145859,0.05762713,0.01280547,0.005877435,0.008250099,0.0008539022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004629756,0.00009589735,0.9611958,0.0001932432,0.0009853031,0.000129233,0.0004115072,0.004391906,0.000922267,0.0009372847,0.001244143,0.02903052],"study_design_scores_gemma":[0.00001680123,0.0005703755,0.9761778,0.00005335042,0.0004046502,0.0003166032,0.002443191,0.01347845,0.002327202,0.0007440031,0.003430028,0.00003762994],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9681898,0.0003338421,0.01796508,0.00007873397,0.00004674698,0.0002416709,0.01061004,0.0001611986,0.002372846],"genre_scores_gemma":[0.9837511,0.000121705,0.005395206,0.00001786619,0.0000182027,0.0002346377,0.01015213,0.0000248361,0.000284233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009993835,"threshold_uncertainty_score":0.05285311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0733477279072504,"score_gpt":0.3441060185546895,"score_spread":0.2707582906474391,"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."}}