{"id":"W2766983581","doi":"10.5004/dwt.2017.20774","title":"Prediction of water aeration efficiency in high turbulent flow","year":2017,"lang":"en","type":"article","venue":"Desalination and Water Treatment","topic":"Hydraulic flow and structures","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Aeration; Turbulence; Environmental science; Flow (mathematics); Mechanics; Environmental engineering; Waste management; Engineering; Physics","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":[0.00004889255,0.0000777602,0.00008837473,0.00005803939,0.00007085942,0.00003536866,0.00003143463,0.00004335458,0.0000206056],"category_scores_gemma":[0.000001698487,0.00004372532,0.00001684256,0.000007268935,0.00001735061,0.0001282679,0.000006497432,0.00002091997,0.000005051362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005264665,"about_ca_system_score_gemma":0.000001730891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007497181,"about_ca_topic_score_gemma":0.00003314468,"domain_scores_codex":[0.9996122,0.00000971887,0.000129386,0.00008577234,0.00006563826,0.00009730368],"domain_scores_gemma":[0.9998313,0.000002735664,0.0000100664,0.0001196431,0.00001540696,0.00002080577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000147396,0.0007158781,0.03561389,0.0003727483,0.0003118755,0.00008043638,0.03967655,0.4655871,0.2467844,0.002489328,0.0003192672,0.2079011],"study_design_scores_gemma":[0.001497179,0.0001449427,0.05744513,0.00001720966,0.00001890964,0.000003550966,0.00002210606,0.1551364,0.784157,0.0004468075,0.001016342,0.00009435228],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981833,0.00002881675,0.0008659221,0.0003001495,0.0001729471,0.0001222505,0.000007487133,0.00003233397,0.0002868504],"genre_scores_gemma":[0.9995345,0.00004615136,0.0001691211,0.000006820841,0.00003229009,0.00001856562,0.00009286091,0.000006207882,0.0000934562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5373726,"threshold_uncertainty_score":0.1783067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01158881444807444,"score_gpt":0.20926926504414,"score_spread":0.1976804505960656,"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."}}