{"id":"W2912724935","doi":"10.1177/1729881418825407","title":"Position deceptive tracking controller and parameters analysis via error characteristics for unmanned aerial vehicle","year":2019,"lang":"en","type":"article","venue":"International Journal of Advanced Robotic Systems","topic":"Guidance and Control Systems","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Calgary; U.S. Department of Homeland Security","keywords":"Computer science; Offset (computer science); Position (finance); Controller (irrigation); Control theory (sociology); Position error; Spoofing attack; Tracking (education); Tracking error; Path (computing); Real-time computing; Artificial intelligence; Control (management); Orientation (vector space); Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003640869,0.0007119472,0.0004523383,0.0006136883,0.0003530932,0.0008737335,0.0005646591,0.0006248099,0.001019594],"category_scores_gemma":[0.001854879,0.0001986485,0.0003865849,0.0003926675,0.0003981619,0.001286057,0.0005311924,0.0009328546,0.0001785508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005280569,"about_ca_system_score_gemma":0.0005220745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004014405,"about_ca_topic_score_gemma":0.001579119,"domain_scores_codex":[0.9994178,0.00004982961,0.00003542653,0.0001106881,0.000348695,0.00003757346],"domain_scores_gemma":[0.9990501,0.0002327692,0.0002244936,0.00009160788,0.000382577,0.00001849959],"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":[0.0001654415,0.00005678317,0.002675214,0.0003033368,0.00005371889,0.0003901772,0.0004635038,0.8266444,0.0383576,0.02328857,0.0009636078,0.1066376],"study_design_scores_gemma":[0.000004937969,0.00008359297,0.0009199778,0.00001323785,0.000008833645,0.0001021721,0.00003987097,0.990999,0.00523304,0.001795513,0.0007849886,0.0000149343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03332299,0.0005375574,0.9616318,0.0001097079,0.00004238249,0.0000336301,0.00002567489,0.0002066603,0.004089584],"genre_scores_gemma":[0.9758914,0.0006098709,0.0197114,0.00005084645,0.0000302216,0.0000674607,0.00007083439,0.00003565631,0.00353228],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004014405,"threshold_uncertainty_score":0.007982075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008130930957312911,"score_gpt":0.2394867202967169,"score_spread":0.231355789339404,"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."}}