{"id":"W4392748168","doi":"10.2166/bgs.2024.051","title":"From shower to table: fate of organic micropollutants in hydroponic systems for greywater treatment and lettuce cultivation","year":2024,"lang":"en","type":"article","venue":"Blue-Green Systems","topic":"Wastewater Treatment and Reuse","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agencia Estatal de Investigación; Horizon 2020 Framework Programme; Ministerio de Ciencia e Innovación; Generalitat de Catalunya; European Commission; Departament d'Innovació, Universitats i Empresa, Generalitat de Catalunya; Centres de Recerca de Catalunya; Canadian Institute for Advanced Research","keywords":"Shower; Greywater; Table (database); Environmental science; Horticulture; Environmental chemistry; Environmental engineering; Chemistry; Biology; Engineering; Computer science; Wastewater","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001655656,0.0002448239,0.0003559909,0.000103434,0.00005541231,0.0001023283,0.0001412814,0.0001033381,0.00005805754],"category_scores_gemma":[0.000005307015,0.0001661568,0.00004715727,0.000294844,0.00005229064,0.0001908827,0.00008441442,0.00004113111,0.0001759493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000470717,"about_ca_system_score_gemma":0.00001758035,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01675672,"about_ca_topic_score_gemma":0.001184467,"domain_scores_codex":[0.9985124,0.00007319768,0.0004152558,0.0005026765,0.000180728,0.0003157695],"domain_scores_gemma":[0.9994856,0.00006197996,0.00006874617,0.0002766779,0.000009040562,0.00009794404],"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":[0.0001092218,0.0001921935,0.03819304,0.0002339697,0.0002124137,0.00004679933,0.006045361,0.001309447,0.9511893,0.00002494194,0.001435332,0.00100799],"study_design_scores_gemma":[0.01533768,0.004837656,0.03426458,0.00627086,0.001122707,0.0002717359,0.01647033,0.06277408,0.6480329,0.0001917015,0.2064437,0.003982019],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954463,0.00165025,0.0002550889,0.0002195863,0.0005336594,0.001460039,0.000263694,0.00004843056,0.0001229543],"genre_scores_gemma":[0.9911786,0.00005059347,0.00007965283,0.000009119845,0.0001477643,0.0001688918,0.00004298761,0.00003877618,0.008283557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3031564,"threshold_uncertainty_score":0.9897908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01351805834300209,"score_gpt":0.2337533309163882,"score_spread":0.2202352725733861,"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."}}