{"id":"W3043167361","doi":"10.15376/biores.15.3.5899-5912","title":"Modelling of dewatering wood pulp in a screw press using statistical and multivariate analysis","year":2020,"lang":"en","type":"article","venue":"BioResources","topic":"Soil, Finite Element Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Pulp (tooth); Multivariate statistics; Screw press; Dewatering; Statistical analysis; Multivariate analysis; Statistical model; Mathematics; Materials science; Pulp and paper industry; Statistics; Engineering; Composite material; Geotechnical engineering","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":[0.0001708086,0.0001210148,0.00027956,0.0001472861,0.00001877368,0.00002921274,0.00008690506,0.00005157081,0.00001468766],"category_scores_gemma":[0.00004432607,0.0001210712,0.00003371589,0.000356764,0.00003066187,0.00005782206,0.00006065155,0.00009008391,4.778879e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001498276,"about_ca_system_score_gemma":0.000003344655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004590098,"about_ca_topic_score_gemma":0.00001022483,"domain_scores_codex":[0.9991696,0.00006188806,0.0002839351,0.000179254,0.0001133342,0.000191917],"domain_scores_gemma":[0.9996443,0.0001321416,0.00003586854,0.00009352047,0.00001216243,0.00008201977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000175003,0.000008184806,0.008139769,0.0001247282,0.0001617232,0.000006906105,0.002379386,0.9747984,0.01326295,0.00004525832,0.000001006556,0.001054223],"study_design_scores_gemma":[0.0002344292,0.00001469913,0.001687291,0.00002478143,0.0001422132,3.648383e-7,0.0001272784,0.9889034,0.008629565,0.00002122607,0.00009014684,0.0001245724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6206068,0.0003029035,0.3789155,0.000005475832,0.00001073356,0.00005310274,0.00001785348,0.00004191577,0.0000457256],"genre_scores_gemma":[0.8597929,0.00002169267,0.1401252,0.000006611267,0.00002702125,0.000003089171,0.000004463794,0.00001824411,7.920526e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2391862,"threshold_uncertainty_score":0.4937141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08900245290934794,"score_gpt":0.285120191897394,"score_spread":0.1961177389880461,"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."}}