{"id":"W3200613921","doi":"10.1109/tii.2021.3114358","title":"Real-Time Optimized Path Planning and Energy Consumption for Data Collection in Unmanned Ariel Vehicles-Aided Intelligent Wireless Sensing","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Informatics","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University; Queen's University Belfast; Royal Academy of Engineering","keywords":"Wireless sensor network; Energy consumption; Computer science; Software deployment; Real-time computing; Wireless; Distributed computing; Intelligent transportation system; Computer network; Engineering; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002246704,0.0001679416,0.0002391336,0.0002111152,0.0001837561,0.0001163359,0.00008782683,0.0002508602,0.00002211608],"category_scores_gemma":[0.00001316798,0.0001949533,0.00003469157,0.0003919209,0.00003189347,0.0003882865,0.000003941749,0.0002298057,0.000003994146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000149446,"about_ca_system_score_gemma":0.00008228287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006281693,"about_ca_topic_score_gemma":0.00001889129,"domain_scores_codex":[0.9988899,0.00003397737,0.0006067144,0.0001470654,0.00012113,0.000201237],"domain_scores_gemma":[0.9992204,0.0002273682,0.00009055476,0.0003139423,0.00007853701,0.00006923493],"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":[0.0001466719,0.00005084359,0.000009001676,0.00005472137,0.00006657647,0.000001451265,0.0009426526,0.9491016,0.001212369,0.00006350247,0.0008317419,0.04751887],"study_design_scores_gemma":[0.001582738,0.0000364224,0.000004184046,0.0001238447,0.00005372922,0.0000118326,0.0005237797,0.9813654,0.01565556,0.00002528109,0.0004231493,0.0001940237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06983373,0.00001488831,0.9290306,0.00003723711,0.0003487623,0.0002743549,0.00008078752,0.0001531521,0.0002264557],"genre_scores_gemma":[0.8795705,0.001358027,0.1171586,0.00008402025,0.0001500753,0.0001422199,0.001101676,0.00009287529,0.0003420193],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.811872,"threshold_uncertainty_score":0.7949964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0612786972041739,"score_gpt":0.2652433720644715,"score_spread":0.2039646748602976,"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."}}