{"id":"W2148495027","doi":"10.5539/mas.v2n4p33","title":"Manpower Management Benefits Predictor Method for Aircraft Two Level Maintenance Concept","year":2008,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computerized maintenance management system; Aircraft maintenance; Computer science; Operations management; Operations research; Management system; Planned maintenance; Process (computing); Reliability engineering; Risk analysis (engineering); Business; Preventive maintenance; Engineering; Aeronautics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004486592,0.0001861842,0.0001862976,0.0001018733,0.0002928702,0.0000411872,0.0004663577,0.000048771,0.00001613578],"category_scores_gemma":[0.00002170719,0.0001741958,0.00005235623,0.0003689018,0.0003240228,0.0002379905,0.0000828898,0.00009850354,0.00001785419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001663742,"about_ca_system_score_gemma":0.00003514725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004353369,"about_ca_topic_score_gemma":0.000004136064,"domain_scores_codex":[0.9983297,0.000005674947,0.000242843,0.0004990169,0.0003671715,0.0005555733],"domain_scores_gemma":[0.9992895,0.00003952241,0.00003791838,0.0004080926,0.0001041289,0.0001208999],"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":[0.00002062123,0.00002847031,0.00001323351,0.00004522713,0.00001194696,0.000001947807,0.0008020898,0.9376131,0.01039715,0.02792704,0.001353748,0.02178541],"study_design_scores_gemma":[0.0007608745,0.00001766209,0.0006388517,0.00002086937,0.000009776073,0.000007369588,0.00005281265,0.9842526,0.0068234,0.005177291,0.001995306,0.0002432392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003086546,0.00006167651,0.9814886,0.00007807154,0.000318957,0.000791375,0.0000376037,0.000288078,0.01384905],"genre_scores_gemma":[0.6316376,0.00006245972,0.367033,0.0001491134,0.00003997554,0.000233705,0.000007134196,0.00002527523,0.0008116786],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6285511,"threshold_uncertainty_score":0.71035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02301731407624138,"score_gpt":0.2458947059188435,"score_spread":0.2228773918426021,"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."}}