{"id":"W3124229413","doi":"10.20944/preprints201807.0630.v1","title":"Cationic High Molecular Weight Lignin Polymer: A Flocculant for the Removal of Anionic Azo-Dyes from Simulated Wastewater","year":2018,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lignin; Cationic polymerization; Chemistry; Flocculation; Polymer; Wastewater; Methyl orange; Pulp (tooth); Polymerization; Reactive dye; Black liquor; Biodegradation; Chloride; Polymer chemistry; Organic chemistry; Dyeing; Catalysis; Waste management; Photocatalysis","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":[0.0002619957,0.0004324659,0.0002296512,0.0003381928,0.0001616797,0.0002760108,0.0002410351,0.0004097139,0.0004942811],"category_scores_gemma":[0.0002137791,0.0001171337,0.0002664258,0.0001971562,0.0001409274,0.0002425134,0.0002650594,0.0003018191,0.0002120547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002155623,"about_ca_system_score_gemma":0.0002346579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008191831,"about_ca_topic_score_gemma":0.001274531,"domain_scores_codex":[0.9998715,0.0000237282,0.00001040126,0.00002258092,0.00004673092,0.00002508906],"domain_scores_gemma":[0.9999321,0.000007845916,0.00002103936,0.000004470191,0.00001661977,0.00001795804],"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":[0.00001846175,0.00002006922,0.00004515871,0.0000505595,0.00000352824,0.00001227681,0.000004403908,0.00005264089,0.9983088,0.00001793354,0.000008028686,0.001458132],"study_design_scores_gemma":[0.000006969427,0.0001478335,0.0005934509,0.000005010621,0.00001345794,0.00004636841,0.000004814845,0.000565889,0.9981194,0.000007914465,0.0004858693,0.000002850488],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894844,0.00236843,0.007234073,0.00008574786,0.00002945088,0.00005708995,0.0000511193,0.00007012232,0.0006196349],"genre_scores_gemma":[0.9908342,0.0009515281,0.006835392,0.00003909073,0.00001106177,0.00001817264,0.00007279586,0.00001634707,0.001221404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008191831,"threshold_uncertainty_score":0.001653492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04098575118964407,"score_gpt":0.287381713146562,"score_spread":0.246395961956918,"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."}}