{"id":"W4414348312","doi":"10.1109/tmc.2025.3612221","title":"Energy-Efficient Multi-UAV Navigation for Cooperative Data Sensing and Transmission","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"China Scholarship Council; National Natural Science Foundation of China","keywords":"Transmission (telecommunications); Data transmission; Signal processing; Signal-to-noise ratio (imaging); Key (lock)","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":[0.0001144415,0.000129912,0.0001220853,0.0001052405,0.0003558,0.00005414957,0.00009109503,0.00006978924,0.000003030981],"category_scores_gemma":[0.000001295949,0.0001371744,0.00002792999,0.0002727932,0.00002547448,0.0000680884,0.000002058666,0.0001053841,9.749186e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005126479,"about_ca_system_score_gemma":0.00001898507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001809141,"about_ca_topic_score_gemma":0.000009263407,"domain_scores_codex":[0.9992865,0.00001940941,0.0002160512,0.0002760063,0.00006035791,0.0001416354],"domain_scores_gemma":[0.9994848,0.0001341745,0.00002192472,0.0002490849,0.00007135293,0.00003869834],"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":[0.000004666532,0.00003256668,3.88848e-7,0.00003253469,0.00001574092,1.111513e-7,0.0001217012,0.6934057,0.002890521,0.00003115735,0.00003184065,0.303433],"study_design_scores_gemma":[0.0004398472,0.00002171875,0.000006541849,0.0001247983,0.00003417818,0.000001858074,0.0001008957,0.9757899,0.02157979,0.000009110445,0.001768438,0.0001229202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01513259,0.0001851118,0.9836362,0.00002611011,0.0002407565,0.0004301082,0.00004578642,0.0002340839,0.00006924644],"genre_scores_gemma":[0.9390799,0.00005856008,0.06062928,0.00002921259,0.00002108761,0.00003024595,0.00007138852,0.00002095064,0.00005940231],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9239473,"threshold_uncertainty_score":0.5593811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01677114046148439,"score_gpt":0.2689798549207823,"score_spread":0.2522087144592979,"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."}}