{"id":"W4214919561","doi":"10.1002/cjce.24396","title":"Modelling textural and mass transfer properties for gamma‐alumina catalysts using randomly generated pore networks","year":2022,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Zeolite Catalysis and Synthesis","field":"Chemistry","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Porosity; Pulsed field gradient; Mass transfer; Diffusion; Materials science; Sorption; Monte Carlo method; Volume (thermodynamics); Helium; Thermodynamics; Chemistry; Composite material; Chromatography; Physical chemistry; Adsorption; Organic chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003247504,0.0001503903,0.0002895723,0.00007292792,0.0002145918,0.000070467,0.0002403881,0.00006023003,0.00003995098],"category_scores_gemma":[0.0000465991,0.0001139303,0.0001566764,0.0001089745,0.00004865655,0.00007216078,0.00001286506,0.0003724012,4.599055e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002216909,"about_ca_system_score_gemma":0.0001818597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005225982,"about_ca_topic_score_gemma":0.00002342203,"domain_scores_codex":[0.9990593,0.00001159319,0.0003409996,0.0001156966,0.0001508496,0.0003215726],"domain_scores_gemma":[0.9994071,0.00007064689,0.00005911017,0.0001227211,0.00007577356,0.0002646243],"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":[0.000053179,0.000002168556,0.000009753378,0.00003849225,0.0000802357,0.00001847262,0.0003344057,0.6998138,0.2994074,0.00001634594,0.00002878606,0.000197009],"study_design_scores_gemma":[0.0004653353,0.00000546082,1.497086e-7,0.00004474815,0.0001217163,0.0002329473,0.00008426026,0.8128304,0.1853117,0.00001235145,0.0007538417,0.0001370345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857571,0.003351992,0.01045217,0.0002470399,0.00007629785,0.00006275301,0.0000244757,0.000008377971,0.00001979267],"genre_scores_gemma":[0.9992086,0.000005694081,0.0003706784,0.00003087047,0.0002746467,0.00001042955,0.00001570925,0.00003466989,0.00004868405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1140956,"threshold_uncertainty_score":0.4645941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02120645409851015,"score_gpt":0.1768338700268482,"score_spread":0.1556274159283381,"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."}}