{"id":"W2322336173","doi":"10.1149/1.3205663","title":"Effective Transport Coefficients for Porous Microstructures in Solid Oxide Fuel Cells","year":2009,"lang":"en","type":"article","venue":"ECS Transactions","topic":"Advancements in Solid Oxide Fuel Cells","field":"Materials Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Microstructure; Solid oxide fuel cell; Discretization; Anode; Monte Carlo method; Knudsen diffusion; Thermal diffusivity; Porosity; Diffusion; Cathode; Porous medium; Mechanics; Electrode; Composite material; Thermodynamics; Chemistry; Mathematics; Physics; Mathematical analysis; Physical chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.0005744578,0.0003067176,0.0004020722,0.0007979391,0.0005495523,0.0007326248,0.000877909,0.0006570814,0.0006954969],"category_scores_gemma":[0.002146507,0.0002719401,0.0003268294,0.0006379581,0.000694931,0.001059779,0.0003854621,0.0004953471,0.0001352764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001451918,"about_ca_system_score_gemma":0.001242227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006213688,"about_ca_topic_score_gemma":0.005375316,"domain_scores_codex":[0.9998567,0.00002676659,0.00000847454,0.00001140565,0.00007603577,0.0000205329],"domain_scores_gemma":[0.9995332,0.0002493328,0.00004161448,0.00002840032,0.0001184869,0.00002906738],"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":[0.00001594951,0.00002186876,0.0004601768,0.00004777018,0.00000780809,0.00007129468,0.00004019925,0.9107241,0.005105021,0.07710255,0.0002015458,0.006201628],"study_design_scores_gemma":[0.000004156866,0.000003739943,0.00006169868,0.000003584294,0.000001705966,0.000009887627,0.000004507053,0.9916248,0.0008056425,0.007245076,0.0002319503,0.000003294143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2248449,0.001053653,0.7666662,0.0001850355,0.00004750899,0.00006781178,0.0001716231,0.0002552058,0.006708039],"genre_scores_gemma":[0.841482,0.0008308178,0.1545369,0.00003885194,0.00002358908,0.0001701042,0.0001922358,0.00008416568,0.002641444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006213688,"threshold_uncertainty_score":0.01235503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007203743949681563,"score_gpt":0.2696843777715338,"score_spread":0.2624806338218523,"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."}}