{"id":"W4386436315","doi":"10.1007/978-981-19-9822-5_237","title":"Optimization of a Powerful Double-Intake and Rotor Squirrel Cage Fan","year":2023,"lang":"en","type":"book-chapter","venue":"Environmental science and engineering","topic":"Turbomachinery Performance and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Latin hypercube sampling; Squirrel-cage rotor; Rotor (electric); Kriging; Impeller; Computational fluid dynamics; Sampling (signal processing); Computer science; Engineering; Marine engineering; Automotive engineering; Mechanical engineering; Mathematics; Aerospace engineering; Electrical engineering; Statistics; Voltage","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":[0.0003845992,0.0006992572,0.0008619307,0.0003171494,0.0004099964,0.0006462603,0.0005985855,0.0008100303,0.005072325],"category_scores_gemma":[0.0005481213,0.0003759171,0.0003870064,0.0003168393,0.0004309987,0.0003413809,0.0005246594,0.0003390211,0.0004797349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004597507,"about_ca_system_score_gemma":0.0005559154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001815882,"about_ca_topic_score_gemma":0.002596747,"domain_scores_codex":[0.9998949,0.00003441809,0.000002397525,0.00001696799,0.00003408107,0.00001721557],"domain_scores_gemma":[0.9998792,0.00006199042,0.00001156331,0.000007816913,0.00002666912,0.00001265094],"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":[0.00007194025,0.00002715218,0.0002063807,0.00005975123,0.00001325107,0.00005588368,0.00001714269,0.978898,0.003258855,0.003976353,0.0006770008,0.01273816],"study_design_scores_gemma":[0.00001105932,0.00005695603,0.0001903936,0.000003941252,0.000003903688,0.00001247285,0.000006310272,0.9979533,0.0004016318,0.0007363426,0.0006205633,0.000003108569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2019894,0.001350025,0.6690382,0.0004235907,0.0002076201,0.0002050302,0.0003029734,0.00052842,0.1259548],"genre_scores_gemma":[0.937321,0.0003349649,0.04436796,0.00004859233,0.00004543259,0.0001345149,0.0001127074,0.0001315571,0.01750316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005072325,"threshold_uncertainty_score":0.01696861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005705099376135512,"score_gpt":0.1685019182106567,"score_spread":0.1627968188345212,"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."}}