{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003414659,0.0004700643,0.0002811146,0.0003291778,0.0002405094,0.0004723539,0.0006625901,0.0004778678,0.006190995],"category_scores_gemma":[0.001141292,0.000110314,0.0001629198,0.0001301285,0.0002068802,0.0008117994,0.001071632,0.0004208541,0.001009972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002106031,"about_ca_system_score_gemma":0.000382277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007563697,"about_ca_topic_score_gemma":0.00102002,"domain_scores_codex":[0.9996092,0.00009616492,0.000009302513,0.00005411088,0.0001556106,0.00007568521],"domain_scores_gemma":[0.9996445,0.0001180882,0.00004876051,0.00004389587,0.00009561032,0.00004923658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000295177,0.0007375148,0.005098652,0.0003140465,0.00002516662,0.0002094375,0.0004469339,0.08798236,0.1059448,0.004753022,0.003228351,0.7909645],"study_design_scores_gemma":[0.0002271643,0.008806893,0.03452332,0.0004074761,0.0001345522,0.001593795,0.001124834,0.6506737,0.15694,0.01110607,0.1343318,0.0001304518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3860734,0.0006863293,0.5614571,0.0007552503,0.0002014697,0.0002251945,0.00007028239,0.002093154,0.04843776],"genre_scores_gemma":[0.9018008,0.0004255089,0.0873422,0.0001264657,0.00006661737,0.00008135397,0.00008602523,0.0001049255,0.009966038],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006190995,"threshold_uncertainty_score":0.02071089,"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."}}