{"id":"W2019833113","doi":"10.1115/ipc2002-27233","title":"Probabilistic Modeling of Corroded Pipeline Structures","year":2002,"lang":"en","type":"article","venue":"4th International Pipeline Conference, Parts A and B","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; TransCanada (Canada); Martec (Canada)","funders":"","keywords":"Corrosion; Randomness; Pipeline (software); Pipeline transport; Probabilistic logic; Computer science; Random field; Field (mathematics); Structural engineering; Engineering; Materials science; Reliability engineering; Metallurgy; Mechanical engineering; Artificial intelligence; 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":[0.0008464782,0.0007982361,0.0008656832,0.0009342413,0.0003805769,0.001036663,0.002171535,0.001453852,0.001400152],"category_scores_gemma":[0.002437288,0.0008574316,0.0008996645,0.001026594,0.0008422831,0.001095497,0.0008088448,0.0006164755,0.0003303067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008486321,"about_ca_system_score_gemma":0.0005717744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01122759,"about_ca_topic_score_gemma":0.006203352,"domain_scores_codex":[0.9995095,0.0001382085,0.00002582414,0.0001173378,0.0001506878,0.0000584028],"domain_scores_gemma":[0.999117,0.0004186133,0.0002018591,0.00006868879,0.0001595659,0.00003420308],"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":[0.000006099969,0.000003254958,0.0002079059,0.00001318264,0.00000730906,0.00005211764,0.00001723591,0.9905342,0.0005048699,0.006932408,0.000113734,0.001607758],"study_design_scores_gemma":[0.00000141262,0.000005455204,0.0001105153,0.000001601243,0.000003433769,0.00001638275,0.000003387847,0.9971126,0.00009399819,0.002454752,0.0001931291,0.000003314105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04687542,0.0006309023,0.9465184,0.0002663141,0.00003283863,0.00003653474,0.0003857246,0.0004306945,0.004823129],"genre_scores_gemma":[0.9297177,0.001830974,0.05654094,0.00006341102,0.00006890044,0.0001617519,0.0006121996,0.0001122018,0.01089205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01122759,"threshold_uncertainty_score":0.0223245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03718732399932575,"score_gpt":0.243853329915235,"score_spread":0.2066660059159092,"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."}}