{"id":"W1975120567","doi":"10.1007/s10898-012-0011-4","title":"Optimization methodology assessment for the inlet velocity profile of a hydraulic turbine draft tube: part II—performance evaluation of draft tube model","year":2012,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Cavitation Phenomena in Pumps","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Polytechnique Montréal","keywords":"Draft tube; Computational fluid dynamics; Inlet; Hull; Grid; Computer science; Tube (container); Turbine; Simulation; Mathematical optimization; Mechanical engineering; Marine engineering; Mathematics; Engineering; Aerospace engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003383738,0.0001857374,0.000391953,0.0001163168,0.00009924766,0.00001798821,0.0002169924,0.000133669,0.00009190519],"category_scores_gemma":[0.0004357719,0.00015305,0.0001292673,0.0004757236,0.00006029353,0.0008127513,0.00004466673,0.0001533431,5.346008e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005464179,"about_ca_system_score_gemma":0.0002233401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003066288,"about_ca_topic_score_gemma":0.000001497039,"domain_scores_codex":[0.9976924,0.0002059311,0.001038672,0.000110643,0.0007025072,0.0002498656],"domain_scores_gemma":[0.9972564,0.0002120661,0.0007634506,0.0002165488,0.001471063,0.00008049857],"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":[0.00008318443,0.0001004652,0.0006244375,0.00007902698,0.0001483921,4.279452e-8,0.0004139701,0.9935969,0.0002526326,0.0003596851,0.0007684379,0.003572827],"study_design_scores_gemma":[0.001297422,0.0002025249,0.001795841,0.00005730985,0.0003778218,0.00001383794,0.00008966999,0.9944767,0.001284484,0.0001808011,0.00009015844,0.0001334754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1014312,0.0005487922,0.8956747,0.0002259124,0.000897696,0.0006833529,0.00005220852,0.0000235542,0.0004625929],"genre_scores_gemma":[0.6250717,0.0001468141,0.3744998,0.00003321541,0.0001416318,0.00003281435,0.00004353702,0.00001979921,0.00001070758],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5236405,"threshold_uncertainty_score":0.62412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05462665995559051,"score_gpt":0.3286806632136798,"score_spread":0.2740540032580893,"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."}}