{"id":"W2062924463","doi":"10.1115/ipc2014-33264","title":"Pipeline Coating Selection Process: A Hybrid Multi-Criteria Based Approach","year":2014,"lang":"en","type":"article","venue":"","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Petroleum Technology Alliance Canada","funders":"","keywords":"Computer science; Analytic hierarchy process; Process (computing); Risk analysis (engineering); Selection (genetic algorithm); Pipeline (software); Structuring; Coating; Reliability engineering; Systems engineering; Management science; Operations research; Engineering; Machine learning; Business","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":[0.008413053,0.002422408,0.00266076,0.006063499,0.001701273,0.005324401,0.003988063,0.003159081,0.004436835],"category_scores_gemma":[0.006650324,0.001297976,0.003311672,0.004008867,0.001100518,0.002167674,0.003710719,0.001740054,0.0005653759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002986246,"about_ca_system_score_gemma":0.005321488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006700289,"about_ca_topic_score_gemma":0.006999767,"domain_scores_codex":[0.9908831,0.003911375,0.0007270689,0.0009075326,0.00287798,0.0006930591],"domain_scores_gemma":[0.995176,0.002573216,0.0004449674,0.0001317035,0.001410718,0.0002634139],"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":[0.0003021759,0.0006126619,0.005752633,0.003651097,0.0009615054,0.001559633,0.002091536,0.7005727,0.01241629,0.02543674,0.003554318,0.2430887],"study_design_scores_gemma":[0.00007965646,0.0005218907,0.001906452,0.0004279968,0.0003302623,0.0002570452,0.001109336,0.9670973,0.002688106,0.01875964,0.006690542,0.0001317292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02217659,0.001785226,0.9661599,0.000686247,0.00006953017,0.001178127,0.0001541174,0.0002411814,0.007549189],"genre_scores_gemma":[0.3501209,0.001106022,0.6426112,0.0003208511,0.00009012264,0.001477827,0.0003493491,0.00007385229,0.003849861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008413053,"threshold_uncertainty_score":0.04449296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01471480539605292,"score_gpt":0.2470499310076407,"score_spread":0.2323351256115878,"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."}}