{"id":"W4391485991","doi":"10.3390/en17030719","title":"An Artificial Neural Network-Based Fault Diagnostics Approach for Hydrogen-Fueled Micro Gas Turbines","year":2024,"lang":"en","type":"article","venue":"Energies","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Research Executive Agency; European Commission; Equinor; Universitetet i Stavanger","keywords":"Artificial neural network; Gas turbines; Fault (geology); Computer science; Artificial intelligence; Environmental science; Engineering; Mechanical engineering; Geology; Seismology","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":[0.00008275056,0.000282553,0.0002510677,0.0001193425,0.0000737648,0.00008100273,0.0003253823,0.0001775904,0.000009202046],"category_scores_gemma":[0.0002645644,0.0002627758,0.0001306584,0.0003609863,0.00008573237,0.0001736857,0.00005155204,0.0002635093,0.000005247716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005660562,"about_ca_system_score_gemma":0.00002367293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000494653,"about_ca_topic_score_gemma":0.000002212078,"domain_scores_codex":[0.9986821,0.00001395163,0.0002792322,0.0004063851,0.0001434746,0.0004748521],"domain_scores_gemma":[0.9990772,0.0003849572,0.00003543329,0.0003815742,0.00005610853,0.00006471201],"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":[0.00001985397,0.00003650157,0.00001479161,0.00009647578,0.00002633942,0.000009362994,0.00003140144,0.915194,0.07020194,0.007932753,0.001173392,0.005263176],"study_design_scores_gemma":[0.0001295094,0.00005134959,0.000003027133,0.00002528541,0.00003106428,0.000003938549,0.00005984058,0.7588444,0.2339689,0.002277179,0.00434704,0.0002585324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5083,0.003084179,0.4796298,0.0003886836,0.0005952307,0.0002816584,0.00004036013,0.00759379,0.00008626035],"genre_scores_gemma":[0.922034,0.00004672175,0.07654142,0.00005703546,0.0006983834,0.0002413831,0.0001690664,0.0001204687,0.00009148202],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.413734,"threshold_uncertainty_score":0.9999824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635878311058577,"score_gpt":0.2544608849230576,"score_spread":0.2381021018124718,"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."}}