{"id":"W2064072957","doi":"10.1016/j.jlp.2011.12.007","title":"Risk analysis for oil & gas pipelines: A sustainability assessment approach using fuzzy based bow-tie analysis","year":2011,"lang":"en","type":"article","venue":"Journal of Loss Prevention in the Process Industries","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":304,"is_retracted":false,"has_abstract":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Fault tree analysis; Event tree analysis; Fuzzy logic; Pipeline transport; Event (particle physics); Event tree; Risk analysis (engineering); Interdependence; Pipeline (software); Engineering; Operations research; Computer science; Business; Reliability engineering; Environmental engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02895176,0.0002931927,0.001239057,0.003027778,0.000514137,0.0003910175,0.001661833,0.0002551162,0.000193305],"category_scores_gemma":[0.008007859,0.0001785976,0.001797064,0.01455061,0.0003031566,0.0009712614,0.00007363241,0.0007539729,0.000001185805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002713884,"about_ca_system_score_gemma":0.001201754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002152986,"about_ca_topic_score_gemma":0.0004154236,"domain_scores_codex":[0.991806,0.002275513,0.002738465,0.0005319006,0.002235389,0.0004127791],"domain_scores_gemma":[0.9896935,0.001651409,0.003717185,0.0008691895,0.003929475,0.0001392716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004167243,0.001015513,0.7397823,0.00004802845,0.002843593,0.000006685133,0.003831965,0.2185634,0.000001436496,0.0001508621,0.00009284007,0.03324668],"study_design_scores_gemma":[0.002992575,0.0004146468,0.2109437,0.00009111714,0.04036024,0.00003378297,0.09160145,0.2093284,0.0002075479,0.4420913,0.001082372,0.0008528519],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4570349,0.0001595943,0.5416595,0.0006311192,0.00005128622,0.0001594574,0.00002946343,0.000006649285,0.0002679673],"genre_scores_gemma":[0.9828851,0.00009372235,0.0164391,0.00003617717,0.0001152984,0.00004181508,0.00001747122,0.00001104655,0.0003603287],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5288385,"threshold_uncertainty_score":0.9998985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1760241213584252,"score_gpt":0.4352446916766376,"score_spread":0.2592205703182123,"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."}}