{"id":"W2585917148","doi":"10.7287/peerj.preprints.2670v1","title":"Signature-based detection of behavioural deviations in flight simulators - Experiments on FlightGear and JSBSim","year":2016,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Crew; Computer science; Flight simulator; Signature (topology); Simulation; Event (particle physics); Real-time computing; Reliability engineering; Engineering; Aeronautics","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":[0.001291789,0.0006003856,0.0004074205,0.00100205,0.0001509845,0.0003380229,0.0009366223,0.0007581031,0.0006707358],"category_scores_gemma":[0.01020118,0.0002663092,0.0004480268,0.0004799762,0.0004244713,0.000628998,0.0005398994,0.0007054584,0.0002199857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003993496,"about_ca_system_score_gemma":0.0004055133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001757412,"about_ca_topic_score_gemma":0.002215117,"domain_scores_codex":[0.9982758,0.000471162,0.0001569588,0.000299138,0.0006562982,0.000140711],"domain_scores_gemma":[0.9923788,0.004326773,0.0008847535,0.001099805,0.0009719103,0.0003378648],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003798352,0.003124466,0.09106165,0.0007616213,0.0003933724,0.0009575182,0.00136986,0.3309097,0.3956153,0.001783924,0.001603491,0.1686207],"study_design_scores_gemma":[0.000105274,0.003483088,0.02780394,0.00002392233,0.00007288628,0.0004472518,0.0001941159,0.8128635,0.1535552,0.0005428422,0.0008510886,0.00005700758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838971,0.00006146521,0.01470073,0.00003266485,0.00001730293,0.00004417157,0.0002152758,0.0008069112,0.0002243337],"genre_scores_gemma":[0.9861648,0.00003173991,0.01318188,0.00001414313,0.000002412851,0.00002336858,0.0002978343,0.000053081,0.0002306393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001757412,"threshold_uncertainty_score":0.006831706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02253402351972562,"score_gpt":0.2591032350340215,"score_spread":0.2365692115142959,"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."}}