{"id":"W3048709413","doi":"10.1109/lra.2020.3015464","title":"Target Search on Road Networks With Range-Constrained UAVs and Ground-Based Mobile Recharging Vehicles","year":2020,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"AUG Signals (Canada); University of Toronto","funders":"","keywords":"Computer science; Rendezvous; Range (aeronautics); Integer programming; Linear programming; Routing (electronic design automation); Real-time computing; Engineering; Computer network; Algorithm","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":[0.00006873644,0.0001143714,0.0001094529,0.00005049782,0.00009574478,0.00009324123,0.00004001359,0.00004117319,0.000006011928],"category_scores_gemma":[0.000002170452,0.0001074662,0.00001385597,0.0001587448,0.0000400299,0.00009317773,0.000004688745,0.0001123813,0.000002991606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000196429,"about_ca_system_score_gemma":0.000006431348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004658328,"about_ca_topic_score_gemma":6.165443e-7,"domain_scores_codex":[0.9994612,0.00001683496,0.0001270853,0.0001563033,0.0001006699,0.0001378507],"domain_scores_gemma":[0.999762,0.00003807359,0.00002535209,0.00007988706,0.0000201911,0.0000745067],"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":[0.000008614685,0.000006223941,0.0001888989,0.00003308708,0.00001219216,0.000001480824,0.0001413277,0.9918957,0.002027763,0.0000811867,0.0003113978,0.005292087],"study_design_scores_gemma":[0.0004133934,0.00005715555,0.001319797,0.00003002681,0.00001012279,0.000001606864,0.00003958174,0.9973763,0.0004912702,0.000002910394,0.0001254139,0.0001324138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2924218,0.00005897084,0.7031456,0.003828753,0.00003537571,0.000236061,0.000004679274,0.0002310243,0.00003777423],"genre_scores_gemma":[0.9647547,0.00003999621,0.03303212,0.002022706,0.0000622921,0.00003054285,0.00003026135,0.00002543057,0.000001936176],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6723329,"threshold_uncertainty_score":0.4382345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009896165271067327,"score_gpt":0.1982288058755922,"score_spread":0.1883326406045249,"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."}}