{"id":"W2319244401","doi":"10.2514/6.2009-5921","title":"Robust Control of a Flight Simulator Motion Base","year":2009,"lang":"en","type":"article","venue":"AIAA Modeling and Simulation Technologies Conference","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute for Christian Studies; University of Toronto","funders":"Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Flight simulator; Computer science; Simulation; Motion control; Base (topology); Motion (physics); Motion simulator; Computer vision; Artificial intelligence; Robot","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":[],"consensus_categories":[],"category_scores_codex":[0.00008308697,0.0001486024,0.0002286169,0.0001814327,0.00005909889,0.00002116478,0.0001313121,0.0002675999,0.000007326783],"category_scores_gemma":[0.0001199439,0.0001445733,0.00003355183,0.0001857302,0.00005612546,0.0001710734,0.00001799771,0.0001710622,0.000003389267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001940569,"about_ca_system_score_gemma":0.000009049206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002787784,"about_ca_topic_score_gemma":0.000001363765,"domain_scores_codex":[0.9992365,0.0000088291,0.0002833339,0.0001896504,0.0001063715,0.0001753786],"domain_scores_gemma":[0.9994847,0.00004973178,0.00005838256,0.0002567826,0.000129029,0.00002142461],"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":[0.000006296333,0.00001109037,0.0002488426,0.00001307758,0.000008186424,5.228769e-7,0.00005341022,0.9391308,0.003586398,0.004405763,0.000003890071,0.05253176],"study_design_scores_gemma":[0.0004262917,0.00006434546,0.00009148673,0.00003024673,0.00001370994,6.570158e-7,0.000229861,0.9833103,0.006194961,0.009476271,0.00001656521,0.0001453236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3679711,0.0002558662,0.6299683,0.0003340562,0.00002533191,0.0001020181,0.000004545918,0.001271934,0.00006690049],"genre_scores_gemma":[0.9978157,0.0001657967,0.001954481,0.0000257147,0.000007722751,0.000004582371,0.000005805187,0.000009818054,0.00001038276],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6298447,"threshold_uncertainty_score":0.5895529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02695185375642622,"score_gpt":0.2226235572191374,"score_spread":0.1956717034627111,"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."}}