{"id":"W2594988625","doi":"10.1177/1748006x17694494","title":"Formal reliability analysis of oil and gas pipelines","year":2017,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Qatar National Research Fund","keywords":"Pipeline transport; Reliability (semiconductor); Computer science; Monte Carlo method; Pipeline (software); Reliability engineering; Environmental science; Engineering; Mathematics; Statistics","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":[0.001924987,0.000641716,0.0003236336,0.001160906,0.0003993219,0.001283263,0.0009525429,0.0004442419,0.001648648],"category_scores_gemma":[0.005161576,0.0002936591,0.001139377,0.0005569766,0.001818982,0.001252882,0.0007492476,0.0008745689,0.0002395548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001530653,"about_ca_system_score_gemma":0.001603611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004444933,"about_ca_topic_score_gemma":0.00218141,"domain_scores_codex":[0.9982316,0.0005398591,0.0001170473,0.0002280468,0.0007037157,0.0001797212],"domain_scores_gemma":[0.996603,0.002140963,0.0003617649,0.000229021,0.000609076,0.00005607447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003761441,0.00005926309,0.0009454495,0.0002759989,0.00003601303,0.0004188892,0.0003735362,0.3787407,0.008281006,0.5902497,0.0006701451,0.01991174],"study_design_scores_gemma":[0.00002458971,0.00006792065,0.0004779587,0.00008357809,0.0000451406,0.0001797182,0.00007708516,0.6671567,0.006846936,0.3152967,0.00971592,0.00002776429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01995159,0.0003301604,0.9740287,0.0001853483,0.00002793309,0.00006343506,0.000157925,0.0003190995,0.004935812],"genre_scores_gemma":[0.7727358,0.001031743,0.2212277,0.000113946,0.0001224747,0.0002585882,0.0004127153,0.0001145889,0.003982455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004444933,"threshold_uncertainty_score":0.01110566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01201272703748745,"score_gpt":0.2573335610753184,"score_spread":0.2453208340378309,"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."}}