{"id":"W2330020580","doi":"10.1115/ipc2010-31646","title":"Statistical Predictive Modelling: A Methodology to Prioritize Site Selection for Near-Neutral pH Stress Corrosion Cracking","year":2010,"lang":"en","type":"article","venue":"2010 8th International Pipeline Conference, Volume 1","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stress corrosion cracking; Integrity management; Pipeline transport; Cracking; Corrosion; Reliability engineering; Probabilistic logic; Reliability (semiconductor); Computer science; Stress (linguistics); Pipeline (software); Ultimate tensile strength; Materials science; Welding; Statistical power; Structural engineering; Forensic engineering; Environmental science; Engineering; Metallurgy; Statistics; Composite material; Mechanical engineering; Artificial intelligence; Mathematics; Power (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005066996,0.001407358,0.001451519,0.002523664,0.0006740141,0.001567673,0.003245735,0.001285661,0.003792913],"category_scores_gemma":[0.0114304,0.001057341,0.001895262,0.001787748,0.000802501,0.001330174,0.002155722,0.001820166,0.0009899046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009994193,"about_ca_system_score_gemma":0.002890576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01238064,"about_ca_topic_score_gemma":0.01115759,"domain_scores_codex":[0.9979733,0.0008055062,0.0001202686,0.0003457259,0.0005938759,0.0001613859],"domain_scores_gemma":[0.9938898,0.004167083,0.000576977,0.0003167014,0.0008902548,0.0001591769],"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":[0.0001331296,0.0000964037,0.005547431,0.0001330424,0.0001550134,0.0001688551,0.0001332569,0.8901181,0.001830368,0.01390717,0.002495189,0.08528209],"study_design_scores_gemma":[0.000006550923,0.00003311665,0.0001806571,0.00001048317,0.00001502891,0.00002231925,0.00001405279,0.9938782,0.0004114231,0.004668397,0.0007513104,0.000008646799],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005090042,0.000107971,0.9926847,0.0001349612,0.00002058587,0.00008792148,0.0001594322,0.0009433421,0.0007710694],"genre_scores_gemma":[0.3155973,0.0004500135,0.6784477,0.0002594124,0.0001297347,0.0006665944,0.001257394,0.0003446006,0.002847326],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01238064,"threshold_uncertainty_score":0.02679712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03936628896850641,"score_gpt":0.2979304038519789,"score_spread":0.2585641148834725,"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."}}