{"id":"W2582857696","doi":"10.1002/cjce.22787","title":"Modelling and optimization of hydrogen yield in membrane steam reforming reactors","year":2017,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Catalysts for Methane Reforming","field":"Chemical Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Steam reforming; Hydrogen production; Membrane reactor; Hydrogen; Yield (engineering); Work (physics); Permeation; Process engineering; Chemical reaction engineering; Scaling; Chemistry; Nuclear engineering; Thermodynamics; Membrane; Materials science; Chemical engineering; Engineering; Physics; Mathematics; Catalysis","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":[0.0004570555,0.0001364614,0.0003073733,0.0002025764,0.00006099248,0.00002295183,0.0004091578,0.000115164,0.000008338033],"category_scores_gemma":[0.0006795393,0.0001081564,0.00008261947,0.00009224599,0.00006202032,0.0002998546,0.0000386985,0.0004495296,2.551596e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002316365,"about_ca_system_score_gemma":0.0001072183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005871442,"about_ca_topic_score_gemma":0.0002142087,"domain_scores_codex":[0.998988,0.000004375124,0.00046614,0.00009271503,0.0001700159,0.0002788097],"domain_scores_gemma":[0.9990569,0.00009139125,0.0002557124,0.0002738447,0.00006087332,0.0002613061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000006582727,0.000002050144,0.00005980762,0.00004751438,0.0000234262,0.0000139526,0.0002521775,0.7336963,0.2655461,0.00006697537,2.62156e-7,0.0002848108],"study_design_scores_gemma":[0.0001869015,0.000006182848,0.000003555934,0.0002918102,0.00002024868,0.00008880154,0.00001863777,0.4477568,0.5514921,0.00001738464,0.00002621451,0.00009136793],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971282,0.0003684821,0.002070486,0.000112625,0.00009083888,0.00005506098,0.000002882136,0.000007473921,0.0001639657],"genre_scores_gemma":[0.9988728,0.00001505227,0.0009585516,0.0000042286,0.0001050781,0.000001093978,0.000001299006,0.0000300417,0.00001191584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.285946,"threshold_uncertainty_score":0.8875903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01694916291537592,"score_gpt":0.2066742293535841,"score_spread":0.1897250664382081,"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."}}