{"id":"W2543342399","doi":"10.1016/j.biortech.2016.10.077","title":"Fractionation and cellulase treatment for enhancing the properties of kraft-based dissolving pulp","year":2016,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Shaanxi University of Science and Technology; Shahjalal University of Science and Technology","keywords":"Cellulase; Pulp (tooth); Fractionation; Chemistry; Kraft process; Kraft paper; Dissolving pulp; Dispersity; Adsorption; Dissolution; Pulp and paper industry; Chromatography; Deinking; Molar mass distribution; Cellulose; Chemical engineering; Organic chemistry; Polymer; Waste management; Dentistry; Waste paper; Medicine","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":[0.0001906921,0.00009817981,0.0001446244,0.0001179134,0.0002054362,0.000009500188,0.0001277436,0.00006566079,0.00001326609],"category_scores_gemma":[0.0004316212,0.00004544878,0.00002845155,0.0001044128,0.0005505272,0.00005149253,0.00007114489,0.00002850388,0.000006017295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009206944,"about_ca_system_score_gemma":0.00003333027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001730708,"about_ca_topic_score_gemma":0.0000451261,"domain_scores_codex":[0.999248,0.00002819537,0.0001698951,0.0002111713,0.0001142339,0.0002285631],"domain_scores_gemma":[0.9993045,0.0002619037,0.0001069982,0.0002198931,0.00008562295,0.00002110093],"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":[0.00003738422,0.00003069409,0.0002547051,0.00002409542,0.000007205464,5.741097e-7,0.00009158556,0.000006419181,0.987961,0.0005256227,0.000007036244,0.01105371],"study_design_scores_gemma":[0.0004339755,0.0002211652,0.00007247601,0.0000583738,0.00001046435,0.000001700683,0.0004189275,0.0001168578,0.9936842,0.0005130321,0.004405783,0.00006303589],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767374,0.001221875,0.01785097,0.003604085,0.00003323842,0.0004198268,0.00001492582,0.0001043076,0.00001330851],"genre_scores_gemma":[0.99818,0.00006534073,0.001257109,0.000009020578,0.0000267176,0.0002453342,5.922687e-7,0.00001036859,0.0002055481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0214425,"threshold_uncertainty_score":0.2028441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02787914347721072,"score_gpt":0.2718287388975853,"score_spread":0.2439495954203746,"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."}}