{"id":"W7144070833","doi":"10.71465/ajaae270","title":"The Role of Machine Learning in Predicting Aircraft Maintenance Needs","year":2021,"lang":"","type":"article","venue":"American Journal of Aerospace and Aeronautical Engineering","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Predictive maintenance; Reliability (semiconductor); Aircraft maintenance; Preventive maintenance; Condition-based maintenance","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":[0.002332424,0.0008485176,0.0005686225,0.00175378,0.0003790359,0.001898256,0.0006838157,0.00129222,0.0006993292],"category_scores_gemma":[0.01427819,0.0003092519,0.0002688573,0.00145942,0.000880012,0.003228905,0.0005912791,0.001838812,0.0003853776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006998632,"about_ca_system_score_gemma":0.0006860966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003773049,"about_ca_topic_score_gemma":0.002522219,"domain_scores_codex":[0.9990813,0.000389732,0.00005316899,0.0001736357,0.0002560996,0.0000461661],"domain_scores_gemma":[0.9884089,0.01001822,0.0005556809,0.0003326609,0.0005593104,0.0001253115],"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":[0.0001573865,0.0002601026,0.05123207,0.0003033497,0.0001362367,0.0001247441,0.0001750849,0.5405082,0.002035666,0.0266278,0.005006564,0.3734328],"study_design_scores_gemma":[0.000008629428,0.00006988168,0.00469991,0.0000715891,0.00001631024,0.00005597276,0.00007474614,0.9417025,0.001192084,0.04928004,0.002798848,0.00002945409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2072699,0.02398931,0.7379515,0.01237383,0.0005538759,0.000112261,0.0009448434,0.0008753762,0.01592919],"genre_scores_gemma":[0.9213561,0.005122981,0.07076182,0.0004331333,0.0006379739,0.00004373647,0.0003970838,0.00003921353,0.001207812],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003773049,"threshold_uncertainty_score":0.01233518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002595717128162669,"score_gpt":0.2112862162805917,"score_spread":0.2086904991524291,"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."}}