{"id":"W4248973633","doi":"10.1504/ijscom.2018.099458","title":"Numerical and experimental comparisons of pressed blades for large Francis turbine runners manufactured with a reconfigurable pressing setup and a conventional setup","year":2018,"lang":"en","type":"article","venue":"International Journal of Service and Computing Oriented Manufacturing","topic":"Cavitation Phenomena in Pumps","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Francis turbine; Finite element method; Pressing; Mechanical engineering; Hydraulic press; Turbine blade; Die (integrated circuit); Hydropower; Range (aeronautics); Process (computing); Engineering; Turbine; Power (physics); Hydraulic turbines; Structural engineering; Computer science; Electrical engineering; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006424458,0.0004861119,0.0004937417,0.0006979277,0.0006635607,0.0007770487,0.0007299999,0.0009556359,0.004221798],"category_scores_gemma":[0.001251174,0.0002916344,0.0005004625,0.0005203421,0.001097838,0.000366906,0.0003080401,0.0004607084,0.0005253447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007379386,"about_ca_system_score_gemma":0.0005787307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005171591,"about_ca_topic_score_gemma":0.01419934,"domain_scores_codex":[0.9996287,0.00002600192,0.0000325264,0.00006963308,0.0001763264,0.00006675951],"domain_scores_gemma":[0.998841,0.000431225,0.0001397992,0.0001962799,0.0003185922,0.00007311412],"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":[0.001534253,0.0004239095,0.007884817,0.0006849435,0.00004585821,0.001058749,0.0008169496,0.2364531,0.7180397,0.001955794,0.001333169,0.02976866],"study_design_scores_gemma":[0.0001602454,0.004391734,0.05306934,0.0001173313,0.0001250473,0.0005083284,0.00167441,0.4372915,0.4957785,0.0004754144,0.006206972,0.0002011188],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891161,0.0001815886,0.006709046,0.00005048177,0.00005343773,0.00003764403,0.0003544546,0.0001780892,0.003319148],"genre_scores_gemma":[0.9913504,0.00007885046,0.006597562,0.000009393002,0.000003289358,0.00002117784,0.000218889,0.00002992809,0.001690505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005171591,"threshold_uncertainty_score":0.01412332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00861782450702188,"score_gpt":0.2479433008353477,"score_spread":0.2393254763283258,"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."}}