{"id":"W2027914131","doi":"10.4043/23844-ms","title":"Arctic Pipeline Integrity Management using Risk Based Integrity Modeling","year":2012,"lang":"en","type":"article","venue":"OTC Arctic Technology Conference","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Intecsea (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Integrity management; Structural integrity; Submarine pipeline; Pipeline transport; Arctic; Pipeline (software); Engineering; Risk analysis (engineering); Reliability engineering; Marine engineering; Forensic engineering; Environmental science; Computer science; Geotechnical engineering; Geology; Structural engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001321709,0.001381958,0.0008674672,0.001242823,0.0006929534,0.002451736,0.001486846,0.001544126,0.002454294],"category_scores_gemma":[0.002117899,0.0006867779,0.001174758,0.0006022095,0.0006848844,0.001641734,0.001809645,0.001169731,0.0002905517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001988608,"about_ca_system_score_gemma":0.001997143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02592919,"about_ca_topic_score_gemma":0.01209393,"domain_scores_codex":[0.9992035,0.0002410921,0.00004810548,0.0001519708,0.0002299925,0.0001252665],"domain_scores_gemma":[0.9988776,0.000382013,0.000285351,0.00007528885,0.0003093418,0.00007044548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006381925,0.000005812139,0.0002723612,0.00000647973,0.000007477053,0.00001677408,0.000008553913,0.996129,0.0001982394,0.001327366,0.00008263469,0.001938838],"study_design_scores_gemma":[7.859119e-7,0.000005981392,0.00005506784,0.000002819889,0.000003663797,0.000003610881,0.000004629821,0.9989451,0.00008415634,0.0007350078,0.0001569121,0.000002332641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07015283,0.0006337728,0.9146701,0.000796998,0.00005370353,0.0001430194,0.0004042062,0.0006274948,0.01251798],"genre_scores_gemma":[0.9491902,0.0004059109,0.04537063,0.00006173352,0.00003345146,0.0001291853,0.0003009698,0.00005893992,0.004449055],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02592919,"threshold_uncertainty_score":0.05155653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03607062556327227,"score_gpt":0.261711633527085,"score_spread":0.2256410079638128,"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."}}