{"id":"W2043125550","doi":"10.1109/tcyb.2014.2347801","title":"Fault Diagnosis in Discrete-Event Systems with Incomplete Models: Learnability and Diagnosability","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Petri Nets in System Modeling","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Learnability; Event (particle physics); Abstraction; Fault (geology); Computer science; Artificial intelligence; Theoretical computer science; Missing data; Complete information; Algorithm; Data mining; Mathematics; Machine learning","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":[0.0009016085,0.0002933064,0.0004096933,0.0001862469,0.0001601637,0.0002029478,0.0005879296,0.0001350089,0.000004684417],"category_scores_gemma":[0.00002899301,0.0002546793,0.00007072429,0.0005134908,0.0001572788,0.0004430268,0.0000131836,0.0004258656,0.00001485802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002315189,"about_ca_system_score_gemma":0.00005196159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009928414,"about_ca_topic_score_gemma":0.0008912248,"domain_scores_codex":[0.9972448,0.000445539,0.0005565325,0.0008088498,0.0005311103,0.0004131897],"domain_scores_gemma":[0.9976519,0.0008638042,0.0001204472,0.00106772,0.0001088122,0.0001873117],"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":[0.00001854974,0.0002414494,0.001769524,0.00008215448,0.00001723425,0.000003935947,0.0007016458,0.9771743,0.000007480106,0.001823853,0.00001425886,0.01814561],"study_design_scores_gemma":[0.0006275931,0.0002934895,0.001242313,0.000192553,0.00001622016,0.0000202309,0.00007007547,0.9946378,0.0002648104,0.001857824,0.0004483785,0.0003286933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.183888,0.00009966781,0.8144649,0.0003003714,0.0002822505,0.0004554886,0.00001349907,0.00013514,0.0003607049],"genre_scores_gemma":[0.9903932,0.00008863514,0.009024218,0.00004770084,0.00003002778,0.0003163115,6.878018e-7,0.00002387525,0.0000752958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8065053,"threshold_uncertainty_score":0.9999905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02417307877214612,"score_gpt":0.2481327352134473,"score_spread":0.2239596564413011,"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."}}