{"id":"W2947704348","doi":"10.1109/icc.2019.8761719","title":"3D Multi-Drone-Cell Trajectory Design for Efficient IoT Data Collection","year":2019,"lang":"en","type":"preprint","venue":"","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Drone; Trajectory; Wireless; Data collection; Integer programming; Coordinate descent; Relay; Backhaul (telecommunications); Base station; Linear programming; Real-time computing; Computer network; Algorithm; Telecommunications","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":[0.0002255193,0.0002148762,0.0002044437,0.0001229411,0.00006724954,0.00006157855,0.0003977209,0.0002700251,0.00007802799],"category_scores_gemma":[0.00001209783,0.0002245103,0.00004963962,0.0001195064,0.00001044467,0.00002452646,0.0001725631,0.0001996356,0.00006606169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000163843,"about_ca_system_score_gemma":0.00008335124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003729823,"about_ca_topic_score_gemma":0.00001684141,"domain_scores_codex":[0.9989868,0.0000179706,0.0002573309,0.0004511508,0.0001009003,0.0001858641],"domain_scores_gemma":[0.9987063,0.00008593233,0.00005670473,0.001037458,0.00007012741,0.00004351501],"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":[0.000006626702,0.00007258221,0.000005604152,0.0002164013,0.00002540294,4.79262e-8,0.00005639404,0.9847765,0.0005786566,0.00001162792,0.01351688,0.0007332885],"study_design_scores_gemma":[0.000448307,0.00001540464,0.0000516885,0.00001914923,0.00005363567,4.145182e-7,0.00001479377,0.9929457,0.001949433,0.000006115774,0.004231574,0.0002637897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001098478,0.000295697,0.9930818,0.00001277884,0.0007586139,0.002301433,0.0001364268,0.0004333725,0.001881416],"genre_scores_gemma":[0.0893262,0.0001678226,0.9041688,0.00001913133,0.0001293929,0.0006333474,0.001503224,0.0001136841,0.003938435],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08891302,"threshold_uncertainty_score":0.9155264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06117792168249734,"score_gpt":0.2621961326945371,"score_spread":0.2010182110120398,"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."}}