{"id":"W2063717531","doi":"10.1016/j.ecoleng.2003.10.003","title":"Feasibility of using ornamental plants (Zantedeschia aethiopica) in subsurface flow treatment wetlands to remove nitrogen, chemical oxygen demand and nonylphenol ethoxylate surfactants—a laboratory-scale study","year":2003,"lang":"en","type":"article","venue":"Ecological Engineering","topic":"Constructed Wetlands for Wastewater Treatment","field":"Environmental Science","cited_by":102,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trent University","funders":"Consejo Nacional de Ciencia y Tecnología; Trent University","keywords":"Effluent; Chemical oxygen demand; Chemistry; Wastewater; Environmental chemistry; Nitrate; Ammonium; Sewage treatment; Pulp and paper industry; Nitrogen; Kjeldahl method; Sewage; Biochemical oxygen demand; Nonylphenol; Environmental engineering; Environmental science; Organic chemistry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000319301,0.0003175163,0.0004765001,0.00006017086,0.00005759752,0.0000248359,0.0001297738,0.0001387213,0.000222328],"category_scores_gemma":[0.00007667331,0.000257134,0.00005200643,0.0002952198,0.00006949958,0.0001006945,0.0001494652,0.0001613596,0.00001210933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000694115,"about_ca_system_score_gemma":0.00001951233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001189741,"about_ca_topic_score_gemma":0.0003602002,"domain_scores_codex":[0.9981906,0.0001096211,0.0004342905,0.0005711752,0.0002361245,0.000458216],"domain_scores_gemma":[0.9993126,0.000102515,0.00006566603,0.0002653581,0.000009673789,0.0002441579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007511773,0.0006090184,0.8521329,0.000006524269,0.00003549455,0.00005516356,0.0006225089,0.01868983,0.1276266,0.000001387789,0.000001036081,0.0001443349],"study_design_scores_gemma":[0.004092105,0.000789665,0.8988802,0.00004340643,0.00006093857,0.00005439471,0.0006029612,0.02045761,0.07440857,0.00004723,0.00003157819,0.0005312762],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998697,0.00003125534,0.0001363132,0.00001266173,0.00007704802,0.0008638896,0.00005563025,0.000044122,0.0000820091],"genre_scores_gemma":[0.986558,0.000006668883,0.01336462,0.00001061269,0.00000676938,0.00002425036,0.000004460268,0.00001938014,0.00000519339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05321808,"threshold_uncertainty_score":0.9999881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01470441901901871,"score_gpt":0.2332532026351194,"score_spread":0.2185487836161006,"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."}}