{"id":"W2029052058","doi":"10.1016/j.carbpol.2015.02.015","title":"Production of cationic xylan–METAC copolymer as a flocculant for textile industry","year":2015,"lang":"en","type":"article","venue":"Carbohydrate Polymers","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":80,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cationic polymerization; Xylan; Copolymer; Flocculation; Gel permeation chromatography; Chemistry; Fourier transform infrared spectroscopy; Reactive dye; Nuclear chemistry; Xylose; Pulp (tooth); Polymer chemistry; Titration; Dyeing; Polymer; Organic chemistry; Chemical engineering; Cellulose","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":[0.000134131,0.0003433093,0.0001924637,0.0002238586,0.0002026561,0.0001822821,0.0001210896,0.0002506564,0.0005899345],"category_scores_gemma":[0.0001273648,0.0001103444,0.0002799285,0.0001798052,0.00009468347,0.0002366531,0.000182062,0.000310905,0.0002235532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001874434,"about_ca_system_score_gemma":0.0002216021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006079027,"about_ca_topic_score_gemma":0.0009594978,"domain_scores_codex":[0.9999391,0.000008047199,0.00000470078,0.00001106164,0.00001956258,0.00001754826],"domain_scores_gemma":[0.9999334,0.000007387751,0.00001473088,0.000005510615,0.00001350693,0.00002553651],"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":[0.00001234107,0.00001470655,0.00002656197,0.00001372433,0.000001386565,0.00001648187,0.000003231698,0.00004030409,0.9992555,0.00002195876,0.000008439192,0.0005852957],"study_design_scores_gemma":[0.000003544134,0.00007737946,0.0003664636,0.000001910237,0.000005739217,0.00002094335,0.000003217918,0.0003461587,0.9988164,0.000005335976,0.0003511437,0.00000175557],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943926,0.0007381362,0.003430245,0.00004847521,0.00003037635,0.00003467983,0.00005379612,0.00003795049,0.00123381],"genre_scores_gemma":[0.9944692,0.0004783098,0.003316805,0.00001795194,0.000009325494,0.00001503937,0.00006350994,0.00001572001,0.001614056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006079027,"threshold_uncertainty_score":0.00197351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04155949227586504,"score_gpt":0.3198379424316513,"score_spread":0.2782784501557863,"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."}}