{"id":"W4402522093","doi":"10.3390/polym16182586","title":"Carboxyalkylated Lignin as a Sustainable Dispersant for Coal Water Slurry","year":2024,"lang":"en","type":"article","venue":"Polymers","topic":"Coal Combustion and Slurry Processing","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Lakehead University","keywords":"Dispersant; Chemical engineering; Coal water; Zeta potential; Coal; Rheology; Slurry; Materials science; Alkyl; Adsorption; Lignin; Suspension (topology); Chemistry; Pulp and paper industry; Organic chemistry; Nanotechnology; Composite material; Nanoparticle; 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":[0.0001714007,0.0002569604,0.0001396638,0.0002932277,0.0001210995,0.0002216741,0.0001887488,0.000269025,0.0007328801],"category_scores_gemma":[0.0001792593,0.0001115208,0.0001821186,0.0001918929,0.0001272803,0.0003516997,0.0002581937,0.0004509784,0.0002651491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001625795,"about_ca_system_score_gemma":0.0001276932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003046121,"about_ca_topic_score_gemma":0.001029773,"domain_scores_codex":[0.9998641,0.00002123217,0.00001054643,0.00002936795,0.00005541429,0.00001937521],"domain_scores_gemma":[0.9999256,0.00001125445,0.00002637594,0.000004363576,0.00002015597,0.00001224029],"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":[0.00002352902,0.00002191799,0.0001642693,0.000117234,0.00000489637,0.00006939696,0.00001942636,0.0001201691,0.9932272,0.0001879361,0.00005880888,0.005985291],"study_design_scores_gemma":[0.000005522879,0.000194637,0.0006331578,0.00001183906,0.00001154118,0.00007650167,0.00002181943,0.001095001,0.9942091,0.00005940221,0.003676574,0.0000050264],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9626421,0.01009884,0.02294406,0.0002964982,0.0001201079,0.00007519619,0.0001452189,0.0001743434,0.003503609],"genre_scores_gemma":[0.9864476,0.00242274,0.008805347,0.00009433505,0.0000264587,0.00002635964,0.00009704188,0.00002050142,0.002059691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007328801,"threshold_uncertainty_score":0.002451718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006269643123740325,"score_gpt":0.2287032343884417,"score_spread":0.2224335912647014,"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."}}