{"id":"W3130992186","doi":"10.1109/tits.2021.3056341","title":"Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":304,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Research (Canada); University of British Columbia","funders":"Ministry of Education, India; Israel Science Foundation; Nanyang Technological University; National Research Foundation Singapore; National Research Foundation","keywords":"Matching (statistics); The Internet; Computer science; Human–computer interaction; Engineering; World Wide Web","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006431087,0.0002883881,0.0004990844,0.0004259409,0.000124142,0.0001652357,0.002687108,0.0002568258,0.00002907645],"category_scores_gemma":[0.0001844615,0.0002979548,0.0001603771,0.00103286,0.00006974036,0.0006155559,0.00003943035,0.0007734689,0.00001975403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001689302,"about_ca_system_score_gemma":0.0002259723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001224471,"about_ca_topic_score_gemma":0.0003176665,"domain_scores_codex":[0.9969057,0.0002842558,0.001105831,0.0007373861,0.0005995728,0.0003672992],"domain_scores_gemma":[0.9976575,0.0002529796,0.0002778046,0.001385888,0.0003387428,0.0000871189],"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":[0.000206107,0.002528314,0.0009724442,0.0007691746,0.0004662216,0.0002902241,0.006958501,0.9196424,0.03242683,0.002570481,0.00047457,0.03269471],"study_design_scores_gemma":[0.0008870569,0.00009320451,0.0006981947,0.0004948582,0.00002450748,0.00003423831,0.001184721,0.8199044,0.1758261,0.0003767085,0.0001334948,0.0003424837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1165674,0.0002020527,0.8812109,0.0003457717,0.0007322835,0.000381282,0.00004064143,0.0004375016,0.00008219875],"genre_scores_gemma":[0.9491432,0.00006509377,0.05036205,0.00004079459,0.000009791298,0.0001142971,0.00006504051,0.00002623461,0.0001734911],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8325759,"threshold_uncertainty_score":0.9999472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04250585342149758,"score_gpt":0.2760528715394896,"score_spread":0.233547018117992,"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."}}