{"id":"W2017903623","doi":"10.1115/1.2039949","title":"Numerical Predictions of Transport Phenomena in a Proton Exchange Membrane Fuel Cell","year":2005,"lang":"en","type":"article","venue":"Journal of Fuel Cell Science and Technology","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Proton exchange membrane fuel cell; Chemistry; Mass transfer; Water transport; Current density; Membrane; Electrochemistry; Mechanics; Transport phenomena; Heat transfer; Current (fluid); Diffusion; Thermodynamics; Environmental science; Environmental engineering; Electrode; Water flow; Chromatography; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005524044,0.0004413834,0.0006634308,0.0004952002,0.0007574647,0.001122296,0.0008924625,0.002188854,0.002657854],"category_scores_gemma":[0.003019515,0.0004406806,0.0006420788,0.0004741428,0.001257717,0.000900493,0.0007250928,0.0008041591,0.000337379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001702203,"about_ca_system_score_gemma":0.001344041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01683523,"about_ca_topic_score_gemma":0.00551942,"domain_scores_codex":[0.9998324,0.00004934498,0.00001017661,0.00002041349,0.00005317412,0.00003449737],"domain_scores_gemma":[0.9991714,0.0004771698,0.00008153659,0.00004239998,0.0001789872,0.00004850355],"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":[0.00001748916,0.00001197549,0.0002017463,0.00001602842,0.000002831906,0.00003137659,0.00001791269,0.9939591,0.0006796491,0.0043292,0.00009271079,0.0006399094],"study_design_scores_gemma":[0.000005754086,0.000004585043,0.00004139814,0.000001871852,7.447296e-7,0.000002796045,0.000005118786,0.999227,0.000120579,0.0004861724,0.0001021017,0.000001897451],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6054731,0.0009481575,0.3333863,0.002163071,0.0002621137,0.0002532225,0.0009959891,0.000551987,0.05596605],"genre_scores_gemma":[0.9666957,0.0003008373,0.02580998,0.0001450058,0.00003422658,0.0002795407,0.0002176654,0.00006088999,0.006456106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01683523,"threshold_uncertainty_score":0.03347445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005121954055936752,"score_gpt":0.1944541585618043,"score_spread":0.1893322045058675,"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."}}