{"id":"W3037657209","doi":"10.1016/j.jngse.2020.103445","title":"Failure pressure prediction by defect assessment and finite element modelling on natural gas pipelines under cyclic loading","year":2020,"lang":"en","type":"article","venue":"Journal of Natural Gas Science and Engineering","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"China Scholarship Council; University of Calgary","keywords":"von Mises yield criterion; Materials science; Internal pressure; Corrosion; Structural engineering; Finite element method; Stress (linguistics); Deformation (meteorology); Cyclic stress; Pipeline transport; Composite material; Engineering; Mechanical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003537625,0.0001821132,0.000242772,0.000170931,0.0001369718,0.0001602183,0.0001336061,0.00006895406,0.000003262633],"category_scores_gemma":[0.00009013704,0.0001348057,0.00007140364,0.0003561719,0.00007907756,0.000600773,0.00004179543,0.0007667615,2.255399e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007831862,"about_ca_system_score_gemma":0.00001859435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005150759,"about_ca_topic_score_gemma":0.000001181334,"domain_scores_codex":[0.9988058,0.00001160276,0.0003074811,0.0001986633,0.0004325738,0.0002438728],"domain_scores_gemma":[0.9994654,0.00009591053,0.00006429701,0.00006329506,0.0001251765,0.0001858855],"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":[0.000009004025,0.000003094196,0.0001530745,0.0000924387,0.00006790962,0.000002693176,0.000200729,0.939111,0.05842145,0.00006888072,0.0001246156,0.001745146],"study_design_scores_gemma":[0.0002034934,0.00008827614,0.0005032932,0.0001151908,0.00008598802,0.00004781167,0.0001927145,0.9944379,0.003551719,0.00006034577,0.0005706625,0.0001426469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9719102,0.006174219,0.01980291,0.001524245,0.0004319841,0.00008003729,0.000005586702,0.00005760771,0.00001314474],"genre_scores_gemma":[0.9956077,0.001078311,0.003029343,0.00009205456,0.0001748457,9.376151e-7,0.00000138194,0.00001038771,0.000005041275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05532689,"threshold_uncertainty_score":0.5497215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01041938461290463,"score_gpt":0.2271564679207664,"score_spread":0.2167370833078617,"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."}}