{"id":"W4396217134","doi":"10.3390/electronics13091721","title":"Explainable Artificial Intelligence Approach for Diagnosing Faults in an Induction Furnace","year":2024,"lang":"en","type":"article","venue":"Electronics","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; University of Windsor","funders":"","keywords":"Interpretability; Artificial neural network; Outlier; Deep learning; Artificial intelligence; Computer science; Machine learning; Harmonics; Fault (geology); Measure (data warehouse); Reliability engineering; Voltage; Data mining; Pattern recognition (psychology); Engineering; Electrical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003665525,0.0006021767,0.0004077806,0.000651701,0.0001958371,0.0005151692,0.0006486677,0.0008586883,0.0009093141],"category_scores_gemma":[0.0013381,0.0001735155,0.0005429902,0.0003295951,0.0004014095,0.0004955605,0.0004047774,0.0009917751,0.00008425925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007439524,"about_ca_system_score_gemma":0.0005522978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006315265,"about_ca_topic_score_gemma":0.004413023,"domain_scores_codex":[0.999818,0.00004347542,0.00001234203,0.00005947748,0.000043115,0.00002355035],"domain_scores_gemma":[0.9995697,0.0002597857,0.0000703301,0.00002284086,0.0000670295,0.00001022561],"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":[0.0001103611,0.0000492315,0.003309739,0.00008576232,0.00006041238,0.0002683296,0.000126886,0.9274676,0.004375927,0.004576661,0.0004879946,0.05908117],"study_design_scores_gemma":[0.000002494594,0.00001264653,0.0004245754,0.000004173733,0.000007377872,0.0000157534,0.00000725422,0.9964435,0.0006212789,0.002312643,0.0001454396,0.000002953842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1705264,0.0008464374,0.8240601,0.0007392255,0.00005195864,0.00006001983,0.0002492077,0.00103789,0.002428703],"genre_scores_gemma":[0.9605541,0.0001796767,0.03791082,0.00008411556,0.00003443543,0.00003412988,0.0001864316,0.00001677507,0.0009995499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006315265,"threshold_uncertainty_score":0.01255703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03748760693804111,"score_gpt":0.2941908501454573,"score_spread":0.2567032432074162,"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."}}