{"id":"W1995889332","doi":"10.1115/ipc2004-0244","title":"Selection of External Coatings for Northern Pipelines: Laboratory Methodologies for Evaluation and Qualification of Coatings","year":2004,"lang":"en","type":"article","venue":"2004 International Pipeline Conference, Volumes 1, 2, and 3","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Pipeline transport; Pipeline (software); Computer science; Environmental science; Selection (genetic algorithm); Construction engineering; Focus (optics); Civil engineering; Marine engineering; Forensic engineering; Engineering; Mechanical engineering; Environmental engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0006925678,0.0001342607,0.0002691249,0.0001445599,0.00005356683,0.00002966481,0.000107164,0.0001172989,0.00002807257],"category_scores_gemma":[0.001018554,0.0001231039,0.00007617635,0.0001167757,0.0001225108,0.0001680621,0.00001403477,0.00008778265,3.636211e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005825202,"about_ca_system_score_gemma":0.00008264243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002548048,"about_ca_topic_score_gemma":0.0004059543,"domain_scores_codex":[0.9989426,0.00003838303,0.0005078183,0.0001966546,0.0002095197,0.0001050271],"domain_scores_gemma":[0.9976227,0.0002368099,0.0002114905,0.00007854831,0.001818635,0.0000317601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006618356,0.0001810563,0.02486606,0.001972379,0.0004056894,2.176816e-7,0.004939673,0.1154867,0.6496143,0.02140394,0.0007163714,0.1797518],"study_design_scores_gemma":[0.002756612,0.0002129643,0.005523226,0.0002606006,0.000292748,0.000005508557,0.001822948,0.81603,0.1276588,0.04437964,0.000729628,0.0003273321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5789758,0.0004086131,0.4196765,0.0001887456,0.0001962709,0.0003125983,0.0001548159,0.000034093,0.00005253305],"genre_scores_gemma":[0.9706154,0.0002053798,0.02877588,0.00001861543,0.0001346718,0.00006116025,0.0001061985,0.00001144393,0.00007125498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7005433,"threshold_uncertainty_score":0.5020031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04115050047693047,"score_gpt":0.3235335654005601,"score_spread":0.2823830649236296,"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."}}