{"id":"W1963535736","doi":"10.1002/cjce.20259","title":"Computational modelling of industrial pulp stock chests","year":2010,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fluid Dynamics and Mixing","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Impeller; Pulp (tooth); Computational fluid dynamics; Mechanics; Orthotropic material; Fluent; Mechanical engineering; Materials science; Computer science; Pulp and paper industry; Engineering; Structural engineering; Physics; Finite element method","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002868284,0.0004948734,0.0006079635,0.0005905545,0.000568067,0.001337998,0.001005842,0.001461592,0.002466313],"category_scores_gemma":[0.0008574671,0.000376848,0.000616049,0.0005844727,0.0008501569,0.0004747203,0.000718788,0.0004742479,0.0002574697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008336568,"about_ca_system_score_gemma":0.0008819489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008443894,"about_ca_topic_score_gemma":0.003514774,"domain_scores_codex":[0.9998177,0.00003714239,0.00001215297,0.00003951103,0.00005234896,0.00004125824],"domain_scores_gemma":[0.9996427,0.0002039031,0.00003946823,0.00003542005,0.00004728939,0.00003116967],"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":[0.00002427592,0.00002360754,0.0007041377,0.00001569168,0.000004430534,0.00009415671,0.000021097,0.9956985,0.001559265,0.0005159099,0.00006965972,0.001269292],"study_design_scores_gemma":[0.000005369081,0.00001500107,0.0003175689,0.000003106968,0.000001738316,0.00001187013,0.00001160921,0.998516,0.0007661225,0.000153363,0.0001948193,0.000003469142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8715405,0.0002572248,0.1112738,0.0001683338,0.00005037503,0.0001766466,0.0007584183,0.0005149849,0.01525975],"genre_scores_gemma":[0.9842504,0.0001020575,0.01237745,0.00002114218,0.000005817245,0.0000978598,0.0002928307,0.00002986559,0.002822429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008443894,"threshold_uncertainty_score":0.0167895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589359908508565,"score_gpt":0.1761177481849063,"score_spread":0.1602241490998206,"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."}}