{"id":"W2913645934","doi":"10.1021/acssuschemeng.8b06355","title":"Preparation and Characterization of Lignin-Containing Cellulose Nanofibril from Poplar High-Yield Pulp via TEMPO-Mediated Oxidation and Homogenization","year":2019,"lang":"en","type":"article","venue":"ACS Sustainable Chemistry & Engineering","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":129,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Ministry of Science and Technology of the People's Republic of China; National Natural Science Foundation of China","keywords":"Lignin; Cellulose; Pulp (tooth); Chemical engineering; Chemistry; Thermal stability; Crystallinity; Sodium hypochlorite; Contact angle; Materials science; Organosolv; Flocculation; Nuclear chemistry; Organic chemistry; Composite material","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002113801,0.0001909538,0.000258822,0.00005939248,0.00008053491,0.00007116493,0.00009161473,0.0001159138,0.00004404856],"category_scores_gemma":[0.0002528085,0.0002092393,0.00001655805,0.0002099109,0.00003809109,0.0006768422,0.0001616723,0.00008453282,0.000004757333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00010895,"about_ca_system_score_gemma":0.00004371051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009337635,"about_ca_topic_score_gemma":3.716034e-7,"domain_scores_codex":[0.9987495,0.00001665506,0.0002993405,0.0003725826,0.0002242681,0.0003376331],"domain_scores_gemma":[0.9991738,0.0001503848,0.0001646573,0.0002096964,0.0002231964,0.00007826983],"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":[0.00003829821,0.00001204132,0.001078877,0.0005298358,0.00001725721,0.000006032207,0.0005053537,0.0006466663,0.9970105,0.00006570274,0.000002487995,0.00008689568],"study_design_scores_gemma":[0.0003083721,0.00004785161,0.001110154,0.00007280579,0.00001612841,0.000002611372,0.0004251119,0.003371428,0.9942129,0.00005863168,0.0001786248,0.0001953882],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935446,0.0003178303,0.005544188,0.00002938251,0.00004939579,0.0003355084,0.00001745032,0.00008991103,0.0000717517],"genre_scores_gemma":[0.998189,0.0001393731,0.0006569595,0.000004171427,0.00007024006,0.00003137429,0.0003346026,0.00002880194,0.00054553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004887229,"threshold_uncertainty_score":0.8532533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00395087965685853,"score_gpt":0.2023480062580337,"score_spread":0.1983971266011752,"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."}}