{"id":"W4225508567","doi":"10.1007/s10489-022-03300-1","title":"Log message anomaly detection with fuzzy C-means and MLP","year":2022,"lang":"en","type":"article","venue":"Applied Intelligence","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Anomaly detection; Data mining; Fuzzy logic; Anomaly (physics); Multilayer perceptron; RADIUS; Software; Cloud computing; Cluster (spacecraft); Artificial intelligence; Artificial neural network; Computer security; Operating system","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":[0.001130678,0.0007478434,0.001023328,0.002291223,0.0008639,0.00125073,0.001336148,0.001294905,0.0009703587],"category_scores_gemma":[0.004761911,0.0003336431,0.0007006343,0.00150261,0.0004539529,0.001217933,0.0007469353,0.001596837,0.0005439874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008253629,"about_ca_system_score_gemma":0.001314132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01036755,"about_ca_topic_score_gemma":0.007635125,"domain_scores_codex":[0.9988025,0.0001381785,0.00009792502,0.0003342142,0.0004867832,0.0001404008],"domain_scores_gemma":[0.997907,0.0007417526,0.0001935133,0.0002289455,0.0008557471,0.00007288071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007334281,0.000269798,0.009329665,0.000122991,0.0001408669,0.0001575052,0.0001528404,0.1027463,0.02531738,0.002297503,0.002722794,0.8560089],"study_design_scores_gemma":[0.000007309543,0.0000433104,0.001865682,0.000006787102,0.0000228832,0.00006041346,0.00001885121,0.9873846,0.009037328,0.001002191,0.0005324693,0.00001816077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06521257,0.0002841998,0.929394,0.0001422754,0.000122824,0.0000654531,0.0001339561,0.003543769,0.001100952],"genre_scores_gemma":[0.64167,0.0001432118,0.3548338,0.00006997478,0.00007636401,0.00009556331,0.0002376992,0.0001124951,0.002760887],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01036755,"threshold_uncertainty_score":0.02061439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008776104311428373,"score_gpt":0.2078669362383619,"score_spread":0.1990908319269335,"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."}}