{"id":"W2271407426","doi":"","title":"16. Efficient Cavitation Detection Technology for Optimizing Hydro Turbine Operation and Maintenance","year":2004,"lang":"en","type":"article","venue":"Tunnelling and Underground Space Technology","topic":"Hydraulic and Pneumatic Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cavitation; Turbine; Vibration; Field (mathematics); Mechanical engineering; Hydraulic turbines; Marine engineering; Engineering; Shock (circulatory); Computer science; Acoustics; Mathematics; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.0001810836,0.0001858752,0.0002505503,0.0003900186,0.0002127559,0.00004676774,0.00007210615,0.0003349501,0.000001281129],"category_scores_gemma":[0.00004503413,0.0001840117,0.00002321857,0.000281003,0.0001215643,0.00007028161,0.00002115264,0.0001903884,0.000005387308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001644323,"about_ca_system_score_gemma":0.00001306392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004588673,"about_ca_topic_score_gemma":0.0001313456,"domain_scores_codex":[0.9991003,0.000008370754,0.0002467923,0.0002754317,0.0000662201,0.0003028281],"domain_scores_gemma":[0.9996356,0.00005462346,0.00005528635,0.0001710293,0.00004059077,0.00004287538],"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":[0.00002057814,0.00003290343,0.0000655202,0.0002853789,0.00006910222,0.000005126535,0.0007475282,0.8420162,0.08475106,0.04993308,0.0000268306,0.0220467],"study_design_scores_gemma":[0.00267481,0.0004632999,0.00003507694,0.0003240026,0.00007081502,0.0004874138,0.005665663,0.8727127,0.05912793,0.0559363,0.001847563,0.0006544628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4302321,0.001017618,0.5664518,0.001203181,0.0001712761,0.0002590952,0.000001345363,0.0005339473,0.0001296265],"genre_scores_gemma":[0.9908066,0.0003422929,0.00859381,0.00001724326,0.00004349256,0.00008968973,0.000005122965,0.00003375973,0.00006795204],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5605746,"threshold_uncertainty_score":0.750378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007240126682155407,"score_gpt":0.2068681449007241,"score_spread":0.1996280182185687,"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."}}