{"id":"W2994834765","doi":"10.1088/1755-1315/405/1/012031","title":"Cavitation erosion prediction based on a multi-scale method","year":2019,"lang":"en","type":"article","venue":"IOP Conference Series Earth and Environmental Science","topic":"Cavitation Phenomena in Pumps","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Andritz (Canada); Polytechnique Montréal","funders":"","keywords":"Cavitation; Erosion; Cavitation erosion; Scale (ratio); Work (physics); Environmental science; Perspective (graphical); Marine engineering; Hydraulic turbines; Scale effects; Computer science; Geotechnical engineering; Civil engineering; Engineering; Geology; Acoustics; Mechanical engineering; Geography; Turbine; Artificial intelligence; Cartography; Geomorphology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001844801,0.0001176253,0.00008830684,0.0000833216,0.0001230339,0.00007643867,0.00009684484,0.00003712446,0.0002167681],"category_scores_gemma":[0.000007999287,0.000115187,0.00001633221,0.000137412,0.0002038069,0.0005599576,0.00002778928,0.00008854505,0.00009738252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005715109,"about_ca_system_score_gemma":0.0000164688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009878615,"about_ca_topic_score_gemma":0.00001312772,"domain_scores_codex":[0.9991061,0.00001765405,0.0001220995,0.0002661258,0.0002816515,0.0002063396],"domain_scores_gemma":[0.9996672,0.00002491524,0.00002412781,0.0001638249,0.000007219462,0.0001127312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001458341,0.00002032777,0.002675743,0.00001383316,0.000001172222,3.465454e-7,0.0005037343,0.03050118,0.9541592,0.00008190321,0.000003849676,0.0120241],"study_design_scores_gemma":[0.0004660151,0.0002419845,0.2933337,0.00002730386,0.000004599838,0.000004286907,0.0007191405,0.5210136,0.183258,0.00004086433,0.0006993474,0.0001910752],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988905,0.00001722207,0.008896924,0.00004086032,0.0002741702,0.000221258,0.0000519042,0.00008647893,0.001506149],"genre_scores_gemma":[0.9844319,0.00003307892,0.01513583,0.00006284616,0.00001116176,0.00001614933,0.00002569901,0.000009218118,0.0002741678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7709012,"threshold_uncertainty_score":0.4697188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01068568032526679,"score_gpt":0.2117792223431773,"score_spread":0.2010935420179105,"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."}}