{"id":"W4408280883","doi":"10.1109/tits.2025.3546088","title":"Enhancing Federated Learning in Connected and Autonomous Vehicles Through Cost Optimization and Advanced Model Selection","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Science and Technology Innovation Foundation of Harbin; National Natural Science Foundation of China","keywords":"Selection (genetic algorithm); Computer science; Artificial intelligence","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":[0.001629747,0.0009050274,0.0009546389,0.0005313719,0.0005463252,0.001114371,0.001583874,0.001004747,0.0007927839],"category_scores_gemma":[0.004421801,0.0004387272,0.0005908628,0.0005318365,0.0008663157,0.001691794,0.001859187,0.001024293,0.0001929734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009877731,"about_ca_system_score_gemma":0.001383307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005636139,"about_ca_topic_score_gemma":0.004485307,"domain_scores_codex":[0.9992424,0.0002744335,0.0000295879,0.0001431632,0.0001883748,0.0001221484],"domain_scores_gemma":[0.9984257,0.0007471959,0.0001721245,0.0002364142,0.0003152936,0.0001033108],"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":[0.00003665099,0.00003668621,0.0005415878,0.00001096723,0.00001517509,0.000031296,0.00002202946,0.9827015,0.0005625495,0.002172622,0.000187523,0.01368149],"study_design_scores_gemma":[0.000002403198,0.00001166704,0.00003440526,0.000001058475,0.000001885421,0.000004984806,0.000005112502,0.9980974,0.0002379528,0.001537777,0.00006408934,0.000001297206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0620721,0.0001271659,0.9356418,0.0002270274,0.000027549,0.00003394466,0.00003119961,0.0004542553,0.00138492],"genre_scores_gemma":[0.9516633,0.00006029246,0.04710755,0.00007018716,0.00001407371,0.00004865586,0.00006692696,0.00003676438,0.0009322902],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005636139,"threshold_uncertainty_score":0.01120663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02312540055782239,"score_gpt":0.2736100502962333,"score_spread":0.2504846497384109,"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."}}