{"id":"W1875240552","doi":"","title":"PEM Fuel Cell Modelling Using Artificial Neural Networks","year":2014,"lang":"en","type":"article","venue":"DergiPark (Istanbul University)","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Proton exchange membrane fuel cell; Transient (computer programming); Artificial neural network; Fuel cells; Chemical energy; Voltage; Unitized regenerative fuel cell; Energy (signal processing); Engineering; Electric potential energy; Automotive engineering; Nuclear engineering; Computer science; Electrical engineering; Chemistry; Chemical engineering; Artificial intelligence","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":[0.0002656778,0.0006942049,0.0006068664,0.0004246253,0.0004273767,0.0008296327,0.001026801,0.001472849,0.002388826],"category_scores_gemma":[0.0008654127,0.0004228336,0.0006112698,0.0005827814,0.0002810058,0.0008379375,0.0004806877,0.0007473585,0.0005816876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006616908,"about_ca_system_score_gemma":0.0005427537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01468679,"about_ca_topic_score_gemma":0.008046193,"domain_scores_codex":[0.9998608,0.00003920338,0.00001026128,0.000028263,0.00004819845,0.00001338241],"domain_scores_gemma":[0.9997838,0.0001085736,0.00002026896,0.000009439776,0.00007146085,0.000006446632],"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":[0.000008236295,0.000005470088,0.00009653778,0.00002159967,0.00000863396,0.00002545418,0.000007212065,0.9953596,0.0003190522,0.0009037532,0.0001432075,0.003101294],"study_design_scores_gemma":[9.655557e-7,0.000002477583,0.0000327131,0.000002567058,0.000001321538,0.000003816666,0.000001204142,0.9991356,0.0001055836,0.000398942,0.0003132279,0.000001673605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06536122,0.003186068,0.8848259,0.0006432331,0.0002353245,0.0001444307,0.00103285,0.0009101171,0.04366088],"genre_scores_gemma":[0.9138008,0.002536117,0.05810121,0.000136341,0.0000923979,0.000579092,0.0008301453,0.00008979568,0.02383412],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01468679,"threshold_uncertainty_score":0.02920264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01173743135337875,"score_gpt":0.1553054704673239,"score_spread":0.1435680391139452,"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."}}