{"id":"W4366382409","doi":"10.4050/f-0077-2021-16829","title":"Updating Rotorcraft Simulation Environments by Using Black-Box Input Filters","year":2021,"lang":"en","type":"article","venue":"","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Fidelity; High fidelity; Black box; Computer science; Nonlinear system; Filter (signal processing); Simulation; Flight simulator; Baseline (sea); Data modeling; Control engineering; Engineering; Artificial intelligence","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":[0.0008370373,0.0006881839,0.0004663737,0.0003790717,0.0003313848,0.000764567,0.0009041039,0.0006454643,0.004199409],"category_scores_gemma":[0.00297325,0.000453907,0.0003361989,0.0001978619,0.0003185885,0.0009186083,0.0006766636,0.0008620408,0.0008246212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005164423,"about_ca_system_score_gemma":0.0007264055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005253693,"about_ca_topic_score_gemma":0.005395511,"domain_scores_codex":[0.9997583,0.00006626861,0.00001689114,0.00004903982,0.00008156426,0.00002800167],"domain_scores_gemma":[0.9986303,0.0006134913,0.0001432667,0.0002425416,0.0003273788,0.00004314176],"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":[0.0001505484,0.0001116078,0.001406573,0.00004825184,0.00002496169,0.00006152999,0.00007887944,0.9437881,0.01045577,0.003325178,0.0006219171,0.03992673],"study_design_scores_gemma":[0.000006127921,0.00001482392,0.00005717369,0.00000203969,0.000002056594,0.000002946182,0.000003015634,0.9963865,0.002902803,0.0001931339,0.0004263255,0.000002919577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03882473,0.00001901959,0.9550314,0.00004754832,0.00003816183,0.00004556179,0.00009873969,0.003804194,0.002090721],"genre_scores_gemma":[0.6646292,0.00004630836,0.3318493,0.00005650135,0.00001725606,0.0001322655,0.0003000667,0.0005211782,0.002447901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005253693,"threshold_uncertainty_score":0.01404846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008990083920554453,"score_gpt":0.2217367976360568,"score_spread":0.2127467137155023,"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."}}