{"id":"W3124511745","doi":"10.1109/tvt.2021.3053536","title":"Delivery Drone Driving Cycle","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Drone; Propeller; Throttle; Automotive engineering; Engineering; Computer science; Driving cycle; Simulation; Turning radius; Real-time computing; Aerospace engineering; Power (physics); Marine engineering; Electric vehicle","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":[0.0001491054,0.0003999475,0.0003153693,0.0003716015,0.0003617918,0.0005311174,0.0005326332,0.0004441879,0.005905075],"category_scores_gemma":[0.0008189311,0.0001600924,0.0003473446,0.0002080592,0.0001803808,0.0004065752,0.0004083104,0.0004359191,0.0008942884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004454528,"about_ca_system_score_gemma":0.0005779535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01082037,"about_ca_topic_score_gemma":0.007655729,"domain_scores_codex":[0.9998857,0.00001619163,0.000006133077,0.00002125465,0.00004660145,0.000024152],"domain_scores_gemma":[0.9997985,0.00006260314,0.00001236573,0.00002577749,0.00007722181,0.00002354542],"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":[0.0003267172,0.0001362784,0.006904948,0.0001931763,0.00004537804,0.0002657839,0.0001813403,0.9463795,0.009162845,0.003565767,0.004519557,0.02831871],"study_design_scores_gemma":[0.00005948488,0.0002274988,0.003285384,0.00002579307,0.00002290133,0.0001075259,0.0001771531,0.9684908,0.01077177,0.001213051,0.01558482,0.00003379502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8420833,0.0002324445,0.08320984,0.0002955034,0.0001222108,0.0005030251,0.004828704,0.002865623,0.06585942],"genre_scores_gemma":[0.9760241,0.0001537985,0.01147953,0.00005040222,0.000004841362,0.000181519,0.002545742,0.0001824531,0.009377526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01082037,"threshold_uncertainty_score":0.02151477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003701492557058116,"score_gpt":0.1825337316612403,"score_spread":0.1788322391041822,"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."}}