{"id":"W3012395393","doi":"10.17660/ejhs.2020/85.1.1","title":"Type of constructed wetlands influence nutrient removal and nitrous oxide emissions from greenhouse wastewater","year":2020,"lang":"en","type":"article","venue":"European Journal of Horticultural Science","topic":"Constructed Wetlands for Wastewater Treatment","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation; Université Laval","funders":"Agriculture and Agri-Food Canada; Université Laval","keywords":"Wastewater; Environmental science; Effluent; Greenhouse; Environmental engineering; Greenhouse gas; Nitrous oxide; Constructed wetland; Typha angustifolia; Sewage treatment; Wetland; Eichhornia crassipes; Macrophyte; Pollutant; Agronomy; Chemistry; Aquatic plant; Ecology","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":[0.0002079051,0.000308187,0.0002674958,0.0001842135,0.0001335846,0.0004742947,0.0001897883,0.000293285,0.0003999996],"category_scores_gemma":[0.0005468386,0.000180563,0.0003379594,0.0001381737,0.0003363335,0.0002292884,0.0002366745,0.0002015315,0.00005974846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003088353,"about_ca_system_score_gemma":0.0002924265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002146934,"about_ca_topic_score_gemma":0.003794991,"domain_scores_codex":[0.9997688,0.00006177532,0.00002056068,0.00004626021,0.00005737548,0.00004525319],"domain_scores_gemma":[0.9995899,0.0001331591,0.0001172982,0.00002204267,0.00006509927,0.00007264884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006179768,0.0001347799,0.01582469,0.00007742189,0.00004666767,0.0001485816,0.00005365114,0.0005488364,0.9800375,0.00002794648,0.00002994988,0.002452039],"study_design_scores_gemma":[0.00005644408,0.002449722,0.5217308,0.00001735605,0.0002374502,0.0003123876,0.000670406,0.00455855,0.4684432,0.00009736827,0.001380377,0.00004597474],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996547,0.00003736077,0.0001767546,0.000005151272,0.000002811021,0.000008275568,0.0000202447,0.000004398941,0.00009030919],"genre_scores_gemma":[0.9992955,0.00006959361,0.0003792986,0.00001163932,0.000001793637,0.00001141855,0.00003994988,0.000003106486,0.0001877318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002146934,"threshold_uncertainty_score":0.004268944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01265095790994261,"score_gpt":0.2120476116122909,"score_spread":0.1993966537023483,"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."}}