{"id":"W4376456745","doi":"10.1109/tits.2023.3271430","title":"Logistics in the Sky: A Two-Phase Optimization Approach for the Drone Package Pickup and Delivery System","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"China Scholarship Council; Natural Science Foundation for Distinguished Young Scholars of Hunan Province; National Natural Science Foundation of China","keywords":"Drone; Notation; Pickup; Simulated annealing; Computer science; Mathematics; Algorithm; Artificial intelligence; Arithmetic","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007937124,0.001140906,0.001244804,0.0005776563,0.0006200664,0.001708907,0.001378678,0.001446094,0.005780268],"category_scores_gemma":[0.000883218,0.0007546145,0.001117163,0.0007563892,0.0005065645,0.001107945,0.001383832,0.00106465,0.0005786538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001122679,"about_ca_system_score_gemma":0.001977114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01316958,"about_ca_topic_score_gemma":0.01023327,"domain_scores_codex":[0.9996454,0.0001380937,0.0000111969,0.00005857274,0.00007783566,0.00006894489],"domain_scores_gemma":[0.999762,0.0001063169,0.00003281738,0.00001297688,0.0000588891,0.00002702565],"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":[0.00004333277,0.00002475922,0.0002046346,0.00005758651,0.00002748434,0.00007355234,0.0000328128,0.9827976,0.0004291369,0.007423874,0.000918785,0.007966507],"study_design_scores_gemma":[0.000007847374,0.00001573246,0.00004599468,0.000003286488,0.00000537141,0.000005791717,0.00001483967,0.9976333,0.00006868852,0.001527511,0.000668385,0.000003283662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02069166,0.0005952361,0.9630944,0.0005447911,0.0000966118,0.0001493661,0.0002162404,0.0002450215,0.01436673],"genre_scores_gemma":[0.6747727,0.001001573,0.3002679,0.0003967743,0.000129926,0.0005717043,0.0004593379,0.0002345176,0.02216552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01316958,"threshold_uncertainty_score":0.02618587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05128302992592292,"score_gpt":0.2945357512435078,"score_spread":0.2432527213175849,"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."}}