{"id":"W4405361017","doi":"10.1115/ipc2024-133557","title":"Verification of Internal Corrosion Through ILI and Non-Destructive Testing: Lessons Learned","year":2024,"lang":"en","type":"article","venue":"","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Gibson Energy (Canada)","funders":"","keywords":"Corrosion; Nondestructive testing; Reliability engineering; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01014358,0.00113055,0.001243526,0.001929583,0.000453308,0.003423099,0.003917245,0.001889963,0.001739345],"category_scores_gemma":[0.01038172,0.0005827409,0.0008628145,0.001185859,0.002476121,0.005140028,0.001898091,0.003013332,0.001340656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00168845,"about_ca_system_score_gemma":0.001609857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004998164,"about_ca_topic_score_gemma":0.004735445,"domain_scores_codex":[0.9931204,0.001352579,0.0003574559,0.0008089907,0.004026447,0.0003341826],"domain_scores_gemma":[0.9833341,0.00427551,0.0009046391,0.001714661,0.009096417,0.0006745892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002080189,0.0008736185,0.01410985,0.001912684,0.00005749788,0.0006394431,0.0014849,0.01154795,0.05747672,0.005918546,0.004040039,0.9017307],"study_design_scores_gemma":[0.0001500032,0.00994129,0.04500699,0.005081884,0.000286762,0.005721527,0.009595508,0.1717563,0.4781484,0.04222331,0.231281,0.0008070261],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1741941,0.05245083,0.7167659,0.01662872,0.001227437,0.0006023895,0.0003581656,0.00347371,0.03429873],"genre_scores_gemma":[0.5621033,0.0255248,0.3991502,0.001793259,0.0005051509,0.000176396,0.0003794962,0.0005703229,0.009797066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01014358,"threshold_uncertainty_score":0.05364501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05370864927666977,"score_gpt":0.3111708457469897,"score_spread":0.2574621964703199,"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."}}