{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004903898,0.0009400889,0.0007785117,0.001529306,0.0009795214,0.001004225,0.001035097,0.0009025343,0.00186945],"category_scores_gemma":[0.003509542,0.0003612078,0.0004521697,0.0008256166,0.0009908293,0.0007254595,0.0009194429,0.001079457,0.001226544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008431508,"about_ca_system_score_gemma":0.00100033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001423777,"about_ca_topic_score_gemma":0.00320954,"domain_scores_codex":[0.9951469,0.0009767313,0.0003333802,0.0004598862,0.002926087,0.000156908],"domain_scores_gemma":[0.9966036,0.0003861186,0.000532285,0.0007902432,0.001583488,0.0001042412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008459031,0.0001652998,0.001348808,0.0004529614,0.0000205372,0.0000783699,0.0001832602,0.000920778,0.951198,0.001347578,0.0008969705,0.04330282],"study_design_scores_gemma":[0.00003791358,0.0005985667,0.003626885,0.00007591258,0.00002898536,0.0003884245,0.00009827976,0.00293909,0.9745752,0.0005193251,0.01707134,0.0000402428],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1504061,0.00521376,0.8260058,0.0003744841,0.0002893274,0.003065735,0.0005314774,0.001247406,0.01286594],"genre_scores_gemma":[0.310445,0.003865541,0.6731765,0.0003330676,0.00008369271,0.003554946,0.0009871912,0.0003253894,0.007228647],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004903898,"threshold_uncertainty_score":0.02593458,"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."}}