{"id":"W2558061214","doi":"10.1007/s10311-016-0598-7","title":"Unwanted metals and hydrophobic contaminants in bioreactor effluents are associated with the presence of humic substances","year":2016,"lang":"en","type":"article","venue":"Environmental Chemistry Letters","topic":"Environmental remediation with nanomaterials","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre de Recherche Industrielle du Québec; Institut National de la Recherche Scientifique","funders":"","keywords":"Leachate; Effluent; Chemistry; Environmental chemistry; Bioreactor; Arsenic; Membrane bioreactor; Contamination; Hydraulic retention time; Humic acid; Chromium; Organic matter; Environmental engineering; Organic chemistry; Environmental science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002115291,0.0003003725,0.0002656861,0.0003174697,0.0002825656,0.0005449072,0.000161376,0.0004093751,0.0009801306],"category_scores_gemma":[0.0003960147,0.0001948278,0.0002430592,0.0002025158,0.0002511193,0.0001868952,0.0002981312,0.0002495935,0.000457624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002858799,"about_ca_system_score_gemma":0.0003395119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001687213,"about_ca_topic_score_gemma":0.002458125,"domain_scores_codex":[0.999648,0.00005649583,0.00002475354,0.00006312509,0.000127742,0.00007986139],"domain_scores_gemma":[0.9997293,0.00004912289,0.00006980266,0.0000240666,0.0000871463,0.00004052981],"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":[0.00008897836,0.00000789245,0.0009223331,0.0000174553,0.000005492517,0.00004107137,0.00001362661,0.00002804831,0.9976544,0.00001659766,0.00002333446,0.001180812],"study_design_scores_gemma":[0.00000191731,0.00005760642,0.004698765,0.000001946114,0.000007263562,0.0001199887,0.0000324357,0.0002129583,0.9944911,0.00002497094,0.0003485876,0.00000254306],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949751,0.0007471349,0.002910623,0.00004926953,0.00001533622,0.00001044295,0.0001082481,0.00005279124,0.001131093],"genre_scores_gemma":[0.9963794,0.0002835969,0.0009897569,0.00003827006,0.000006525593,0.000005924239,0.0001737532,0.00001528154,0.002107515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001687213,"threshold_uncertainty_score":0.003354788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003794776357493571,"score_gpt":0.1594727265364695,"score_spread":0.155677950178976,"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."}}