{"id":"W2770505324","doi":"10.1002/srin.201700074","title":"Review of Modeling and Simulation of Galvanizing Operations","year":2017,"lang":"en","type":"article","venue":"steel research international","topic":"Metallurgical Processes and Thermodynamics","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Polytechnique Montréal","funders":"","keywords":"Dross; Galvanization; Coating; Materials science; Metallurgy; Computer simulation; Zinc; Turbulence; Intermetallic; Process engineering; Flow (mathematics); Mechanical engineering; Mechanics; Engineering; Composite material; Layer (electronics); Simulation; Alloy","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":[0.0006160611,0.001584778,0.00216406,0.001444515,0.0005123021,0.001927451,0.002803443,0.002261579,0.006617107],"category_scores_gemma":[0.001779968,0.0009416699,0.00182165,0.002322549,0.0006840058,0.001674024,0.0008286676,0.001247047,0.003063293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001102844,"about_ca_system_score_gemma":0.001757042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01120801,"about_ca_topic_score_gemma":0.004604453,"domain_scores_codex":[0.9994975,0.0001079668,0.00005801541,0.00007332416,0.0002131472,0.00005001041],"domain_scores_gemma":[0.9991931,0.0003526521,0.00006158479,0.00006326206,0.0002986591,0.00003070447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003868508,0.00004161059,0.0009123608,0.00185289,0.00008386481,0.0002053508,0.00007463439,0.8400091,0.00122275,0.04064763,0.01347791,0.1014332],"study_design_scores_gemma":[0.00002037134,0.0000339137,0.0007146324,0.0006138153,0.0000553886,0.0001911586,0.00005816944,0.7854012,0.000995724,0.03388349,0.1779805,0.00005170403],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.0105679,0.2319762,0.6567406,0.003079972,0.002919515,0.0002463628,0.0031022,0.001919258,0.08944797],"genre_scores_gemma":[0.260898,0.4455005,0.22497,0.001157358,0.004028296,0.001118813,0.006480502,0.001668467,0.05417809],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01120801,"threshold_uncertainty_score":0.02228552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1237658334540551,"score_gpt":0.4232825615089926,"score_spread":0.2995167280549375,"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."}}