{"id":"W2963678124","doi":"10.1109/iwcmc.2019.8766627","title":"Hopfield Neural Network-based Fault Location in Wireless and Optical Networks for Smart City IoT","year":2019,"lang":"en","type":"article","venue":"","topic":"Optical Network Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; École de Technologie Supérieure","funders":"","keywords":"Computer science; Artificial neural network; Quality of service; Smart city; Fault (geology); Computer network; Distributed computing; Transmission (telecommunications); Wireless network; Wireless; Internet of Things; Artificial intelligence; Embedded system; Telecommunications","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":[0.0004308562,0.000403134,0.000360332,0.0004602747,0.0003257937,0.0004510943,0.0007791704,0.0005862053,0.0007187398],"category_scores_gemma":[0.001131495,0.0001967157,0.0003257034,0.0003724853,0.0004389437,0.0009333681,0.0003948847,0.0004457321,0.0000776448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001325521,"about_ca_system_score_gemma":0.0008530225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01575357,"about_ca_topic_score_gemma":0.01152686,"domain_scores_codex":[0.9998273,0.00002999936,0.00001285587,0.00003855412,0.00005792635,0.00003339032],"domain_scores_gemma":[0.9997287,0.0001121798,0.00004664153,0.00001414295,0.00008402973,0.0000143372],"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":[0.00007023323,0.00002935373,0.001186269,0.00003152789,0.00002493355,0.0000505571,0.00003622151,0.9314355,0.002230333,0.003092189,0.0004517077,0.06136115],"study_design_scores_gemma":[0.000001977804,0.000007390603,0.00009765422,0.000001482463,0.000004103013,0.000005820496,0.000003362011,0.9986361,0.0003943011,0.0007909185,0.00005470711,0.000002259258],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0805635,0.0006645446,0.9152365,0.0002581217,0.00005316162,0.00003633763,0.00003827467,0.0003530841,0.002796386],"genre_scores_gemma":[0.9615651,0.0002669651,0.03609194,0.00006254528,0.00002311879,0.00004285997,0.00004792084,0.00001287371,0.001886612],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01575357,"threshold_uncertainty_score":0.03132373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00939132417533639,"score_gpt":0.2113738351522238,"score_spread":0.2019825109768874,"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."}}