{"id":"W2325586691","doi":"10.2166/wst.2013.272","title":"Perspectives on modelling micropollutants in wastewater treatment plants","year":2013,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydromantis Environmental Software Solutions (Canada); Université Laval","funders":"Institut National de Recherche en Sciences et Technologies pour l'Environnement et l'Agriculture; Canadian Water Network; National Health and Medical Research Council; Canada Research Chairs","keywords":"Sewage treatment; Biochemical engineering; Wastewater; Environmental science; Computer science; Environmental engineering; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001571224,0.001173307,0.00133352,0.000594491,0.0006073997,0.002922705,0.002191394,0.003621567,0.001866811],"category_scores_gemma":[0.002537665,0.0006269341,0.001762303,0.001259272,0.0009933874,0.003067036,0.001123324,0.001702083,0.0004268479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001645713,"about_ca_system_score_gemma":0.001556301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0187834,"about_ca_topic_score_gemma":0.01091863,"domain_scores_codex":[0.9992873,0.0003400132,0.00005653321,0.00009627277,0.0001731126,0.00004680001],"domain_scores_gemma":[0.9987487,0.000827284,0.00009065471,0.00008065034,0.0002040694,0.00004869368],"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":[0.00002919231,0.00004276337,0.0008092592,0.0002166503,0.00003352677,0.00008481073,0.0000751671,0.9614149,0.002664935,0.02413235,0.0005760657,0.009920502],"study_design_scores_gemma":[0.00001465269,0.00007594667,0.0002599907,0.000053707,0.00001876575,0.00003500612,0.0000722675,0.9700223,0.001362568,0.02089149,0.007163997,0.0000293493],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06378897,0.009288713,0.890661,0.008373978,0.0003109497,0.0002037985,0.001555605,0.0009794696,0.02483757],"genre_scores_gemma":[0.6155883,0.02287978,0.3494888,0.0009536513,0.000452125,0.0006728467,0.00126027,0.0002671221,0.008437022],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0187834,"threshold_uncertainty_score":0.03734809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02025920841293215,"score_gpt":0.2544667609322434,"score_spread":0.2342075525193112,"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."}}