{"id":"W2992022061","doi":"10.2175/193864716819706923","title":"Optimization of ABMet Biological Selenium Removal through Advanced Process Modelling","year":2016,"lang":"en","type":"article","venue":"Proceedings of the Water Environment Federation","topic":"Selenium in Biological Systems","field":"Nursing","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hydromantis Environmental Software Solutions (Canada)","funders":"","keywords":"Selenium; Process (computing); Biochemical engineering; Computer science; Environmental science; Process engineering; Engineering; Materials science; Metallurgy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006071294,0.0009185501,0.00111378,0.0004194287,0.0004962123,0.001552836,0.0007718333,0.00116383,0.001861165],"category_scores_gemma":[0.001169241,0.0004837453,0.001057607,0.0004643819,0.0003119584,0.00067078,0.0006332111,0.0008583945,0.000367763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001061601,"about_ca_system_score_gemma":0.001640085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01427987,"about_ca_topic_score_gemma":0.008527225,"domain_scores_codex":[0.9997188,0.0000620014,0.00001361595,0.00005344295,0.00009505726,0.00005698311],"domain_scores_gemma":[0.9995822,0.0002415884,0.00003502394,0.00002888184,0.00009822416,0.00001409219],"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":[0.00005743287,0.00003455511,0.0002617346,0.00003654051,0.00000930077,0.00002315784,0.00001117023,0.9916596,0.003277741,0.000383913,0.00005989727,0.004184882],"study_design_scores_gemma":[0.000007604046,0.00003575252,0.00009128472,0.000001971767,0.000005009859,0.000003397304,0.000006465742,0.9969614,0.002394663,0.0002250283,0.0002643049,0.000003071761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4974032,0.0007283005,0.4762045,0.0005173617,0.0001116511,0.0001993327,0.0005578612,0.001161495,0.0231163],"genre_scores_gemma":[0.9692361,0.0001673582,0.02708955,0.00002765116,0.000006384829,0.0001312388,0.0001842673,0.00005870813,0.003098668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01427987,"threshold_uncertainty_score":0.02839351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02463872177664151,"score_gpt":0.2266269774254073,"score_spread":0.2019882556487658,"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."}}