{"id":"W3135312670","doi":"10.1063/5.0036138","title":"High-solids enzymatic hydrolysis of biomass: Hydrodynamics and reaction kinetics integration via numerical modeling","year":2021,"lang":"en","type":"article","venue":"Physics of Fluids","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Slurry; Computational fluid dynamics; Total dissolved solids; Mass transfer; Viscosity; Suspended solids; Newtonian fluid; Chemical engineering; Chemistry; Thermodynamics; Chromatography; Physics; Environmental science; Wastewater; Environmental 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":[0.00005301307,0.0001047849,0.0001954418,0.00004833275,0.00001832663,0.000008010109,0.00004396651,0.00007015606,0.000006099479],"category_scores_gemma":[0.00001249078,0.0001064381,0.00005665427,0.000257571,0.00003121936,0.0001291717,0.00002385496,0.00008609378,0.000001945184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003185287,"about_ca_system_score_gemma":0.000007550046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003629306,"about_ca_topic_score_gemma":9.770754e-7,"domain_scores_codex":[0.9993716,0.0000176957,0.0002507241,0.0001343572,0.0001380273,0.00008760847],"domain_scores_gemma":[0.9996352,0.0000137048,0.00004037187,0.0001778169,0.000100869,0.00003202965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005777076,0.0000577237,0.00001610659,0.0002269161,0.00003856087,3.219138e-7,0.0001304032,0.01635425,0.9781598,0.0002781935,0.00001582838,0.004716138],"study_design_scores_gemma":[0.00009674658,0.00002350654,0.00002474947,0.00001850929,0.00003400512,0.000002055682,0.00003485206,0.5892941,0.4092132,0.001183989,0.00001218346,0.0000620836],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7474596,0.000196726,0.2518636,0.00007504534,0.0002051696,0.00004501747,0.000005760896,0.00004289539,0.0001062021],"genre_scores_gemma":[0.9956594,0.0001772798,0.003974599,0.000005670666,0.00008837184,0.000001943034,0.00006977376,0.00001492574,0.000008071836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5729399,"threshold_uncertainty_score":0.434042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00963543901204551,"score_gpt":0.2055266320993494,"score_spread":0.1958911930873039,"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."}}