{"id":"W3134213182","doi":"10.1109/jiot.2020.3030064","title":"Joint UAV Position and Power Optimization for Accurate Regional Localization in Space-Air Integrated Localization Network","year":2020,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Real-time computing; GNSS applications; Position (finance); Power (physics); Constraint (computer-aided design); Metric (unit); Dilution of precision; Global Positioning System; Telecommunications; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005474156,0.0009160702,0.0008358792,0.0004381694,0.0004021864,0.0007097404,0.0008025339,0.0006592539,0.001073787],"category_scores_gemma":[0.001438168,0.0003353169,0.0005617847,0.0006550343,0.0005089486,0.0007445709,0.0008567655,0.0006181528,0.0001863407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007390213,"about_ca_system_score_gemma":0.0009570672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006993791,"about_ca_topic_score_gemma":0.005387336,"domain_scores_codex":[0.9996792,0.00008959757,0.00001558661,0.00008720902,0.00006734583,0.00006111708],"domain_scores_gemma":[0.9996407,0.0001773881,0.0000643021,0.00002761985,0.00006507508,0.00002481307],"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":[0.00003167415,0.00001346321,0.0004356062,0.00002319338,0.00001515327,0.00003646903,0.00003164419,0.9752401,0.001098197,0.002142425,0.0004072758,0.02052493],"study_design_scores_gemma":[0.000005085198,0.00001808459,0.00008280082,0.000001825743,0.000004709121,0.000009625011,0.000008434848,0.9987373,0.000245963,0.0007387794,0.0001453367,0.000002119153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02713449,0.0002515077,0.9706666,0.0001050046,0.00002762207,0.0000314434,0.00002864473,0.0001744338,0.001580191],"genre_scores_gemma":[0.8473943,0.0002152792,0.1499773,0.00008429738,0.00002517796,0.0001569733,0.0001018019,0.00004952554,0.00199529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006993791,"threshold_uncertainty_score":0.01390618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01533500153200785,"score_gpt":0.2193006677644222,"score_spread":0.2039656662324143,"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."}}