{"id":"W3199699300","doi":"10.1007/s12649-021-01579-8","title":"Two-Step Modification Pathway for Inducing Lignin-Derived Dispersants and Flocculants","year":2021,"lang":"en","type":"article","venue":"Waste and Biomass Valorization","topic":"Lignin and Wood Chemistry","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Dispersant; Flocculation; Lignin; Chemical engineering; Polymer; Monomer; Acrylamide; Polymerization; Depolymerization; Kraft paper; Materials science; Chemistry; Suspension (topology); Organic chemistry; Composite material; Dispersion (optics)","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":[0.0001916972,0.0006225049,0.000330416,0.0003032396,0.000247152,0.0002383423,0.0003963753,0.0004414001,0.0009209153],"category_scores_gemma":[0.0001524741,0.0002144612,0.0004013438,0.000202141,0.0001778131,0.0003967378,0.000471475,0.000892258,0.0004983684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002890553,"about_ca_system_score_gemma":0.0004657022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005286976,"about_ca_topic_score_gemma":0.001151733,"domain_scores_codex":[0.9998344,0.00001574532,0.00001239956,0.00004047377,0.00004542991,0.00005149101],"domain_scores_gemma":[0.9999267,0.000008464116,0.00001806286,0.00001286298,0.00001729514,0.00001661894],"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":[0.00005195514,0.00007808254,0.0001088657,0.00008903411,0.00001192789,0.00009898347,0.00004069206,0.0002132516,0.9926727,0.0008056248,0.0001707255,0.005658079],"study_design_scores_gemma":[0.00001077018,0.0001210658,0.0003082479,0.000003028214,0.00001033004,0.00006132087,0.00001071481,0.0006549835,0.9965889,0.0001012777,0.00211913,0.00001022421],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8556127,0.001623598,0.1322102,0.0004352261,0.0002192907,0.0006537678,0.0007197889,0.001030104,0.007495377],"genre_scores_gemma":[0.9534977,0.0007953899,0.0392619,0.000086176,0.00001408798,0.0002019182,0.0003515,0.00005672857,0.005734513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009209153,"threshold_uncertainty_score":0.003080785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01668542128165848,"score_gpt":0.2249922572169632,"score_spread":0.2083068359353047,"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."}}