{"id":"W2745943370","doi":"10.11159/ffhmt17.139","title":"Optimizing Airlift Pumps for Aquaculture Applications","year":2017,"lang":"en","type":"article","venue":"Proceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer","topic":"Oil and Gas Production Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Airlift; Aquaculture; Environmental science; Process engineering; Marine engineering; Petroleum engineering; Computer science; Fishery; Engineering; Bioreactor; Fish <Actinopterygii>; Chemistry; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006492674,0.0006888979,0.0005253016,0.000520329,0.000344821,0.0009065419,0.0003575837,0.0006363686,0.001055753],"category_scores_gemma":[0.0008237106,0.0002841674,0.0003338254,0.0003276783,0.0002336604,0.0006915007,0.0003471507,0.0003764789,0.0003565336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003517051,"about_ca_system_score_gemma":0.000682077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001042188,"about_ca_topic_score_gemma":0.001532616,"domain_scores_codex":[0.9997134,0.000051721,0.00001577521,0.00004612162,0.0001295982,0.00004349359],"domain_scores_gemma":[0.9997162,0.0001238005,0.00006068183,0.00001443229,0.00007289984,0.00001187168],"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":[0.0003503893,0.0002971288,0.004215918,0.000685552,0.00004868401,0.0001908661,0.0000912016,0.5040668,0.3420899,0.001270047,0.0007340495,0.1459594],"study_design_scores_gemma":[0.00004947664,0.0007828144,0.004397624,0.00002334224,0.00003614335,0.00008990063,0.00008922569,0.8344573,0.155913,0.0006040701,0.003526758,0.00003039801],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6576939,0.001080076,0.3361448,0.0001810991,0.00003225345,0.0001674892,0.0001644497,0.0007443104,0.003791744],"genre_scores_gemma":[0.9072527,0.0005187803,0.08998835,0.00002644574,0.000009612769,0.0001493418,0.0001287971,0.00008208734,0.00184391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001055753,"threshold_uncertainty_score":0.003531814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02322884886559678,"score_gpt":0.2518399060157013,"score_spread":0.2286110571501045,"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."}}