{"id":"W2581969751","doi":"10.1016/j.engfailanal.2017.01.018","title":"Revised burst model for pipeline integrity assessment","year":2017,"lang":"en","type":"article","venue":"Engineering Failure Analysis","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Pipeline (software); Pipeline transport; Finite element method; Structural engineering; Engineering; Corrosion; Reliability engineering; Forensic engineering; Mechanical engineering; Materials science; Metallurgy","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004100665,0.0003346868,0.0007030775,0.0003683616,0.0003166609,0.0002939823,0.0006403591,0.0002388028,0.00009507638],"category_scores_gemma":[0.0002952443,0.0003018672,0.0009059512,0.0003967082,0.00005203511,0.0003010297,0.00006111248,0.0005776889,0.000008507138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001648915,"about_ca_system_score_gemma":0.00002267572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001012402,"about_ca_topic_score_gemma":0.0003089745,"domain_scores_codex":[0.9985338,0.00001159173,0.0004440211,0.0003731963,0.0002424475,0.0003948865],"domain_scores_gemma":[0.9983482,0.0001011461,0.00009061801,0.001131669,0.0001731754,0.000155189],"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":[0.000003261023,0.00001225856,0.0009241826,0.0001284383,0.001658608,0.000001633812,0.00005890601,0.9930939,0.001003933,0.0009745368,0.001346044,0.0007942776],"study_design_scores_gemma":[0.0002156026,0.000008434298,0.00228123,0.0000276051,0.002063105,8.518833e-7,0.00002544768,0.9914504,0.0004866323,0.0002611199,0.002815479,0.0003640605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03249982,0.0001551272,0.9650116,0.001038971,0.0002168116,0.0002022296,0.00009859401,0.0004141406,0.000362694],"genre_scores_gemma":[0.9351663,0.00006322507,0.06375307,0.00002076649,0.0001968161,0.00006104924,0.0001086317,0.00003891996,0.0005912268],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9026664,"threshold_uncertainty_score":0.9999433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01849855030262768,"score_gpt":0.2767408277848269,"score_spread":0.2582422774821993,"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."}}