{"id":"W2097137869","doi":"10.1109/adfsp.1998.685710","title":"Comparison of the use of neural networks versus statistical models in fault detection for cable television networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Optical Network Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Fault (geology); Fault detection and isolation; Computer science; Sensitivity (control systems); Artificial neural network; Amplifier; Real-time computing; Statistical model; SIGNAL (programming language); Fault model; Artificial intelligence; Electronic engineering; Engineering; Telecommunications; Bandwidth (computing); 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":[0.002484685,0.0007256085,0.0005255165,0.0009463179,0.0002043332,0.0006042543,0.0005432459,0.0007839951,0.0006115481],"category_scores_gemma":[0.01206057,0.0002645086,0.0003598687,0.0004815505,0.0003252652,0.001535437,0.0004393682,0.0004285983,0.0001412224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007126786,"about_ca_system_score_gemma":0.0004703781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006641088,"about_ca_topic_score_gemma":0.005785466,"domain_scores_codex":[0.9987489,0.0006823132,0.00005714906,0.0001125876,0.0003115483,0.00008747313],"domain_scores_gemma":[0.99063,0.007860651,0.0003713082,0.0003321229,0.0007234823,0.00008257043],"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":[0.000811562,0.0001408329,0.005455698,0.0001122688,0.0001677713,0.00006543307,0.00006190177,0.784932,0.004019468,0.002382642,0.0003632591,0.2014871],"study_design_scores_gemma":[0.000006391078,0.00006422499,0.0005435624,0.000004126803,0.00001408123,0.00001539068,0.00000738868,0.9972534,0.001510246,0.0004901626,0.00008429793,0.000006821835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3199864,0.001323474,0.6744976,0.0005166464,0.0000640797,0.00005795288,0.00008825036,0.001109525,0.002356019],"genre_scores_gemma":[0.9408244,0.000402531,0.05775132,0.00005223388,0.00002913484,0.00003285959,0.00007121911,0.00003996963,0.0007962642],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006641088,"threshold_uncertainty_score":0.01320487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08343005184924186,"score_gpt":0.2762404317004455,"score_spread":0.1928103798512037,"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."}}