{"id":"W2140659059","doi":"10.2514/6.2011-1603","title":"Enhancing Remotely Piloted Vehicle Training","year":2011,"lang":"en","type":"article","venue":"Infotech@Aerospace 2011","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Training (meteorology); Computer science; Remote sensing; Aeronautics; Engineering; Geology; Meteorology; Geography","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":[0.000118993,0.0001732059,0.0001578044,0.00009521565,0.00009732862,0.00003037227,0.0001890787,0.0001467168,0.0004900778],"category_scores_gemma":[0.00001918293,0.0001877377,0.00004680322,0.0002254699,0.00003584562,0.0002444857,0.00003039467,0.000201966,0.0006440693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005283321,"about_ca_system_score_gemma":0.00001995493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001478086,"about_ca_topic_score_gemma":0.00009165865,"domain_scores_codex":[0.9991289,0.000009912957,0.0002434039,0.0001798588,0.0001216011,0.0003162854],"domain_scores_gemma":[0.999404,0.00002026402,0.00004864121,0.0003705327,0.00005562985,0.0001009377],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001078852,0.0003042659,0.002648729,0.0003241607,0.0003684756,0.00003955971,0.05910954,0.0551018,0.7156981,0.01658066,0.01613953,0.1335773],"study_design_scores_gemma":[0.002268627,0.0003527598,0.0505832,0.0002370236,0.000135796,0.00005095946,0.002617644,0.2569711,0.6445155,0.003291442,0.03635677,0.002619176],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4971719,0.0002467661,0.4492097,0.00008291056,0.000399126,0.0004128707,0.00001022447,0.002114208,0.05035224],"genre_scores_gemma":[0.9496069,0.0000688833,0.04970047,0.00006544322,0.00007098425,0.00002793655,0.000008998083,0.00006024633,0.0003901599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4524349,"threshold_uncertainty_score":0.8278423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03343533130659577,"score_gpt":0.1983797719766669,"score_spread":0.1649444406700711,"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."}}