{"id":"W2051798269","doi":"10.1109/acc.2012.6315194","title":"A generalized delay-timer for alarm triggering","year":2012,"lang":"en","type":"article","venue":"","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Honeywell (Canada); University of Alberta","funders":"","keywords":"Timer; ALARM; Computer science; Constant false alarm rate; False alarm; Markov process; Process (computing); Real-time computing; Markov chain; Algorithm; Artificial intelligence; Embedded system; Mathematics; Machine learning; Engineering; Statistics; Programming language; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001046491,0.00007562852,0.0001067558,0.00003620585,0.000029341,0.00001590136,0.00003818665,0.00004476284,0.0001278813],"category_scores_gemma":[0.000006129827,0.00006540603,0.00006870485,0.0000506565,0.000002930994,0.0000914682,0.000003811619,0.00003197126,0.0001087085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002421655,"about_ca_system_score_gemma":0.00000190384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001732765,"about_ca_topic_score_gemma":0.000005520903,"domain_scores_codex":[0.9995446,0.000006589524,0.0001211869,0.00005163332,0.00004965756,0.0002263628],"domain_scores_gemma":[0.9997995,0.00001845184,0.000008075083,0.00008786431,0.00001094476,0.00007520323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002305235,0.0001781245,0.001325773,0.0005379373,0.001241976,0.000003525612,0.002095544,0.0373376,0.5860652,0.02010567,0.1487459,0.2021322],"study_design_scores_gemma":[0.001058489,0.00001289045,0.00006695403,0.000004160388,0.00001576288,0.00001267155,0.00004184797,0.3148279,0.01495166,0.0000173916,0.6688204,0.000169828],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6367394,0.003571115,0.2919418,0.000121618,0.005768002,0.001063727,0.00001088033,0.002398724,0.05838479],"genre_scores_gemma":[0.9953362,0.000007108055,0.001208996,0.00006470592,0.0005219998,0.0001381536,0.000001714028,0.00002421392,0.002696954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5711135,"threshold_uncertainty_score":0.2667181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01422887388175305,"score_gpt":0.2328619950496476,"score_spread":0.2186331211678945,"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."}}