{"id":"W4244062956","doi":"10.1109/iat.2004.1342989","title":"Using event-streams for fault-management in MAS","year":2004,"lang":"en","type":"article","venue":"Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Dependability; Software deployment; Computer science; Fault management; Event (particle physics); Component (thermodynamics); Key (lock); Fault (geology); Domain (mathematical analysis); Distributed computing; Reliability engineering; Computer security; Software engineering; 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":[0.003350514,0.0007068616,0.0006889862,0.001034048,0.0006852242,0.002438321,0.0012997,0.001175374,0.002195878],"category_scores_gemma":[0.00781091,0.0003352693,0.0004478628,0.000796859,0.001019718,0.003555812,0.001182533,0.001379577,0.0005616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008953519,"about_ca_system_score_gemma":0.0005834042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001463754,"about_ca_topic_score_gemma":0.001255429,"domain_scores_codex":[0.9982581,0.0007726341,0.0002095864,0.0002067182,0.0004599195,0.00009313779],"domain_scores_gemma":[0.9946554,0.00328826,0.0004875789,0.0007034517,0.0006671303,0.0001983287],"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":[0.002033925,0.0006240527,0.005164491,0.0007494491,0.0001977422,0.001017453,0.001550555,0.3886481,0.02902031,0.1437596,0.006212254,0.4210222],"study_design_scores_gemma":[0.0001786255,0.0002202384,0.0004310673,0.00006162778,0.00007609377,0.0001717831,0.00009107753,0.9002659,0.02565587,0.05939662,0.01339988,0.00005112091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02512338,0.0005752548,0.9676675,0.0003762707,0.0001688954,0.0002123269,0.0001123593,0.003776883,0.00198709],"genre_scores_gemma":[0.6424792,0.0007886692,0.3533974,0.0002143785,0.0001742466,0.0003200624,0.0002740503,0.0002042043,0.002147752],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003350514,"threshold_uncertainty_score":0.01771939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0746979333111402,"score_gpt":0.3345895578323503,"score_spread":0.2598916245212101,"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."}}