{"id":"W2922033671","doi":"10.1016/j.scitotenv.2019.133772","title":"Mechanisms of pharmaceutical and personal care product removal in algae-based wastewater treatment systems","year":2019,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":78,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"University of Toronto; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Personal care; Wastewater; Algae; Environmental impact of pharmaceuticals and personal care products; Product (mathematics); Sewage treatment; Business; Chemistry; Pulp and paper industry; Biochemical engineering; Environmental science; Medicine; Biology; Engineering; Environmental engineering; Ecology; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004807987,0.0001856824,0.0002125347,0.00003023956,0.0001126441,0.00001635957,0.0004206809,0.00002953465,0.0004571766],"category_scores_gemma":[0.000009919047,0.0000947554,0.00007561208,0.0001782585,0.001988575,0.0001391047,0.0004804221,0.0001135813,0.00008865786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003901519,"about_ca_system_score_gemma":0.00002158322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001754529,"about_ca_topic_score_gemma":7.422366e-7,"domain_scores_codex":[0.9980662,0.00009726603,0.0002598986,0.0004046191,0.0007837027,0.0003883137],"domain_scores_gemma":[0.999324,0.00003856472,0.0001077971,0.0004037733,0.000001719081,0.0001241604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005026033,0.0002073755,0.001923198,0.00003240396,0.000007927896,0.000002464985,0.0007444643,0.04184684,0.9538446,0.0001098883,0.00000252427,0.001228059],"study_design_scores_gemma":[0.0009803929,0.0003292662,0.06425694,0.00006582653,0.00004829079,0.00004763342,0.0008085874,0.03475778,0.8982749,0.0001073189,0.0001271756,0.0001959117],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970397,0.0002011589,0.000005551227,0.0006520164,0.0001568086,0.0007134243,0.00001338982,0.000004577121,0.001213334],"genre_scores_gemma":[0.9991915,0.0000331234,0.0001798769,0.00002911509,0.000007516402,0.000005989309,7.23187e-7,0.000009414204,0.0005427683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06233374,"threshold_uncertainty_score":0.7326988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01857969914131159,"score_gpt":0.2504205762833072,"score_spread":0.2318408771419956,"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."}}