{"id":"W3104037746","doi":"10.1002/cjce.23932","title":"Discolouration of contaminated water with textile dye through a combined coagulation/flocculation and membrane separation process with different natural coagulants extracted from <scp> <i>Moringa oleifera</i> </scp>   <i>Lam</i> . seeds","year":2020,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Coagulation and Flocculation Studies","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Moringa; Microfiltration; Flocculation; Chemistry; Coagulation; Chromatography; Pulp and paper industry; Membrane; Water treatment; Food science; Environmental engineering; Organic chemistry; Biochemistry; Environmental science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001652874,0.0004982249,0.0003612932,0.000271674,0.0001979427,0.0003076125,0.0001955162,0.0003814657,0.000467694],"category_scores_gemma":[0.0001300406,0.0001621376,0.0004780028,0.000188092,0.000152444,0.000224392,0.0002057983,0.0003089519,0.0001827466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002434068,"about_ca_system_score_gemma":0.0002084281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001713626,"about_ca_topic_score_gemma":0.002454676,"domain_scores_codex":[0.9998734,0.00001667784,0.000008742479,0.00002858165,0.00004253365,0.00003011977],"domain_scores_gemma":[0.9999377,0.000009471953,0.00002081049,0.000004507817,0.00001442193,0.00001311077],"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":[0.00004471203,0.00001400226,0.00008767827,0.00003156273,0.00000484516,0.00001871083,0.00001132061,0.00003182166,0.9987653,0.000008787679,0.00000776886,0.0009733802],"study_design_scores_gemma":[0.000005775013,0.0001447037,0.001694052,0.000003780807,0.00001678188,0.00003716262,0.00000995319,0.0004575056,0.9973159,0.000004750958,0.0003065765,0.000003033091],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959092,0.0007477489,0.002720616,0.0000322281,0.00001442511,0.00002803532,0.00005066098,0.0000463059,0.0004506158],"genre_scores_gemma":[0.9939358,0.0005827723,0.003816063,0.00004174889,0.00000586942,0.00002259313,0.00008573549,0.00001832766,0.001491134],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001713626,"threshold_uncertainty_score":0.0034073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008665317557918592,"score_gpt":0.1976136607801621,"score_spread":0.1889483432222435,"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."}}