{"id":"W4295025151","doi":"10.1016/j.cej.2022.139079","title":"Tuning transport mechanisms in fuel-assisted solid oxide electrolysis cells for enhanced performance and product selectivity: Thermodynamic and kinetic modeling","year":2022,"lang":"en","type":"article","venue":"Chemical Engineering Journal","topic":"Catalysts for Methane Reforming","field":"Chemical Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Methane; Syngas; Electrolysis; Anode; Steam reforming; Solid oxide fuel cell; Hydrogen; Chemical engineering; Oxide; Carbon fibers; Water-gas shift reaction; Raw material; Hydrogen production; Carbon monoxide; Chemistry; Process engineering; Energy carrier; Materials science; Catalysis; Organic chemistry; Electrode; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005681982,0.0003060849,0.0004788481,0.000286298,0.0001205274,0.00002397806,0.000195049,0.00007944672,0.000009324631],"category_scores_gemma":[0.00008763605,0.0003216004,0.0001122356,0.0003882317,0.00001649862,0.0001953266,0.00008291274,0.001037271,1.92437e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003912724,"about_ca_system_score_gemma":0.000042303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001057576,"about_ca_topic_score_gemma":9.84892e-7,"domain_scores_codex":[0.9981613,0.00001371235,0.0004904052,0.0004102463,0.0002921152,0.0006322084],"domain_scores_gemma":[0.9994425,0.00008414221,0.00009500262,0.0001596271,0.00004484531,0.0001739434],"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":[0.00006393236,0.00002551918,0.000007831147,0.0002003288,0.00004705493,0.00000690398,0.0002134687,0.2158278,0.7815635,0.00002138984,1.642992e-7,0.002022083],"study_design_scores_gemma":[0.0006355782,0.00003242776,0.00002166507,0.00005296845,0.00003923212,0.0003024185,0.00002416115,0.5350699,0.463551,0.00004961917,0.000005955916,0.0002150214],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7721341,0.0003282366,0.2271696,0.00002219084,0.00007263609,0.0001760257,0.000004376284,0.0000813169,0.00001154222],"genre_scores_gemma":[0.9909568,0.00006309563,0.008647523,0.00001022492,0.00008795489,0.0001037155,0.00001357112,0.00009162894,0.00002547901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3192421,"threshold_uncertainty_score":0.9999236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006395022585301448,"score_gpt":0.1986178124402609,"score_spread":0.1922227898549595,"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."}}