{"id":"W2049284748","doi":"10.1139/l05-029","title":"An improved model for predicting the efficiency of hydraulic propeller turbines","year":2005,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Cavitation Phenomena in Pumps","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Turbine; Hydraulic turbines; Hydroelectricity; Marine engineering; Field (mathematics); Propeller; Operating point; Computer science; Test data; Performance prediction; Power (physics); Engineering; Reliability engineering; Simulation; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003252084,0.0001334752,0.0001801284,0.000247823,0.00005291731,0.00003680422,0.0003010541,0.00004863723,0.00001982241],"category_scores_gemma":[0.0001165016,0.0001107344,0.00008598821,0.0001707902,0.00002403497,0.0002730463,0.000004214062,0.0001875224,7.069134e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001380543,"about_ca_system_score_gemma":0.000209579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005595273,"about_ca_topic_score_gemma":0.007686888,"domain_scores_codex":[0.9990854,0.000005740346,0.000429319,0.00007316379,0.0001103086,0.0002960945],"domain_scores_gemma":[0.9992495,0.00006170788,0.0000899292,0.0001681768,0.0001571517,0.0002735891],"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":[0.000002195251,0.000004202078,0.00004909395,0.00006084587,0.00002762404,8.046995e-7,0.001758851,0.9872165,0.009739814,0.00009363498,0.0002717172,0.0007747297],"study_design_scores_gemma":[0.0002632507,0.00005099742,0.0001554785,0.00005400685,0.00002325956,0.00002105268,0.00007919202,0.9957774,0.001807233,0.00004900491,0.001601031,0.0001181319],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4853237,0.002261272,0.5092284,0.0003384703,0.0009911067,0.0005036913,0.00004768644,0.00008833859,0.001217367],"genre_scores_gemma":[0.9966541,0.000007077131,0.002875663,0.00002655343,0.0003403224,0.00000991261,0.000001485743,0.00004881386,0.0000361051],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5113304,"threshold_uncertainty_score":0.4515619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008365100188241395,"score_gpt":0.1913747818873427,"score_spread":0.1830096816991013,"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."}}