{"id":"W2149679658","doi":"10.1109/tai.1999.809800","title":"Monitoring of aircraft operation using statistics and machine learning","year":2003,"lang":"en","type":"article","venue":"","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; Machine learning","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":[0.001576899,0.0007395483,0.0007542457,0.002492137,0.0002741816,0.001162438,0.0005650074,0.0005952229,0.000459531],"category_scores_gemma":[0.007890738,0.000228947,0.0004193708,0.00158614,0.0006391628,0.001826579,0.0003512834,0.000633585,0.0003446389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004954066,"about_ca_system_score_gemma":0.0006187051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002188632,"about_ca_topic_score_gemma":0.002060095,"domain_scores_codex":[0.9985151,0.0004820375,0.0001226397,0.0001895325,0.000634442,0.00005627138],"domain_scores_gemma":[0.9924929,0.00539137,0.0008465459,0.0005516944,0.0006434441,0.00007417267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002760906,0.0002814681,0.02885795,0.0003037115,0.0001899993,0.0001765056,0.0002116073,0.3345902,0.02000766,0.01681147,0.002778988,0.5955144],"study_design_scores_gemma":[0.00002024949,0.0004062109,0.01240213,0.00007139378,0.00006084428,0.0002940398,0.00007702212,0.9398751,0.01896765,0.02054976,0.007181268,0.00009443321],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04838147,0.001480587,0.9442059,0.0004815387,0.00007883967,0.00005771792,0.0002695549,0.001847384,0.003196933],"genre_scores_gemma":[0.7369513,0.002465286,0.2578068,0.0001924505,0.0003760511,0.0001276061,0.0007539035,0.0001236241,0.001203058],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002492137,"threshold_uncertainty_score":0.008339524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01418988189123005,"score_gpt":0.2310307353389816,"score_spread":0.2168408534477516,"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."}}