{"id":"W2471505370","doi":"10.1017/s000192400000419x","title":"Adaptive moving average for trending of accident rates","year":2010,"lang":"en","type":"article","venue":"The Aeronautical Journal","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Civil Aviation Organization","funders":"","keywords":"Accident (philosophy); Metric (unit); Computer science; Measure (data warehouse); Moving average; Event (particle physics); Aviation; Statistics; Real-time computing; Mathematics; Operations management; Engineering; Data mining; Aerospace engineering; Physics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005077263,0.00009929304,0.0002920347,0.0001366213,0.0004367642,0.0001918508,0.000924365,0.00005987265,0.0009920015],"category_scores_gemma":[0.002762004,0.00004887036,0.0003539075,0.0003343819,0.0001894223,0.0002304939,0.0001150899,0.0004855478,0.00004909794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001706174,"about_ca_system_score_gemma":0.00006732113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007861796,"about_ca_topic_score_gemma":0.00006129688,"domain_scores_codex":[0.9978036,0.0001837086,0.0006753984,0.000168591,0.0009086069,0.0002600946],"domain_scores_gemma":[0.9953669,0.003555315,0.0003234196,0.0003258619,0.0002838472,0.0001446111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009382604,0.000267723,0.02160024,0.000003318067,0.0004455799,0.00003438754,0.003698212,0.005444668,0.03317843,0.1441983,0.006763681,0.7834272],"study_design_scores_gemma":[0.001101229,0.0003221899,0.09959193,0.00002636994,0.0001993273,0.0002411381,0.002788076,0.07423783,0.008091446,0.8064999,0.006646927,0.0002536359],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8296445,0.0001535363,0.1582727,0.009616556,0.0006866385,0.0001177558,0.000007676499,0.000009709006,0.001490893],"genre_scores_gemma":[0.9942526,0.00004294164,0.004711839,0.000106458,0.0002859395,0.000002145445,3.141723e-7,0.00000643544,0.0005913818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7831736,"threshold_uncertainty_score":0.9999212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1026355582672294,"score_gpt":0.4096458642086785,"score_spread":0.3070103059414491,"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."}}