{"id":"W3010002345","doi":"10.1021/acsabm.0c00041","title":"Potential of Xylanases to Reduce the Viscosity of Micro/Nanofibrillated Bleached Kraft Pulp","year":2020,"lang":"en","type":"article","venue":"ACS Applied Bio Materials","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of British Columbia","funders":"State Key Laboratory of Polymer Materials Engineering; Canada First Research Excellence Fund; National Natural Science Foundation of China","keywords":"Kraft process; Cellulose; Kraft paper; Pulp (tooth); Xylanase; Composite material; Viscosity; Materials science; Pulp and paper industry; Softwood; Cellulose fiber; Xylan; Apparent viscosity; Lignin; Chemical engineering; Fiber; Chemistry; Organic chemistry","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":[0.000126281,0.0002822875,0.0001439135,0.0001105736,0.0000791696,0.0002196975,0.0001103384,0.0001760711,0.0005288563],"category_scores_gemma":[0.000151622,0.0001136467,0.0001840322,0.00008164614,0.0001463877,0.0001836675,0.00008601427,0.0003236101,0.0000945677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001335937,"about_ca_system_score_gemma":0.0001398191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005326302,"about_ca_topic_score_gemma":0.0009765439,"domain_scores_codex":[0.9999471,0.000009387877,0.000003826311,0.0000101711,0.00001504623,0.00001455791],"domain_scores_gemma":[0.9999394,0.00001622849,0.00001601284,0.000003957209,0.00001374406,0.00001069107],"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":[0.00006049174,0.00001824983,0.00004700895,0.00002089645,0.00000267417,0.0000125527,0.00000630452,0.00006242176,0.9986023,0.00002159935,0.000004330633,0.001141206],"study_design_scores_gemma":[0.000003511405,0.0001610811,0.000637342,0.00000210434,0.000005159645,0.00001702314,0.000005083394,0.000252119,0.9986733,0.000008209875,0.0002338558,0.000001318619],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995504,0.001462667,0.002206813,0.00004189739,0.00001146263,0.00001528878,0.00004271184,0.00002227897,0.0006928098],"genre_scores_gemma":[0.9943044,0.0008439347,0.003529854,0.00002267859,0.000004428561,0.00001128352,0.00007415627,0.00001102807,0.00119821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005326302,"threshold_uncertainty_score":0.001769125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02440771301453352,"score_gpt":0.2795632022668936,"score_spread":0.25515548925236,"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."}}