{"id":"W7117544024","doi":"10.1109/icscn67106.2025.11308604","title":"A Survey on Multi Metric Clustering and Routing Optimization in Vehicular Ad Hoc Networks","year":2025,"lang":"","type":"article","venue":"","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Cluster analysis; Routing (electronic design automation); Metric (unit); Vehicular ad hoc network; Network packet; Intelligent transportation system; Node (physics); Stability (learning theory); Routing protocol","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":[0.001174865,0.001474622,0.001487495,0.002296528,0.0005293329,0.001769264,0.001365045,0.00131797,0.002765323],"category_scores_gemma":[0.002514848,0.0006121857,0.0008780826,0.007875972,0.000506411,0.002361453,0.0008103927,0.001259289,0.001640215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008888723,"about_ca_system_score_gemma":0.001079824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002257608,"about_ca_topic_score_gemma":0.001786753,"domain_scores_codex":[0.9989021,0.0002918224,0.000125418,0.0001758023,0.0004411117,0.00006378587],"domain_scores_gemma":[0.9988217,0.0005852864,0.00006605617,0.00009304182,0.0003977585,0.00003605471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007058935,0.0001387844,0.001364219,0.004935306,0.0001420962,0.0001211677,0.0001438609,0.04180408,0.001341731,0.04416509,0.03964932,0.8661237],"study_design_scores_gemma":[0.00002757924,0.0004508387,0.002701824,0.002762211,0.0001825995,0.001068197,0.0004324706,0.1260789,0.002733895,0.08636584,0.7770472,0.0001483952],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003823424,0.704262,0.2622398,0.002325023,0.001782194,0.0001403447,0.0003198276,0.0003854397,0.02472191],"genre_scores_gemma":[0.0393055,0.8276275,0.1194561,0.0009332998,0.002757938,0.0001815783,0.001051367,0.0001769188,0.008509822],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002765323,"threshold_uncertainty_score":0.009250939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0139185030886386,"score_gpt":0.2378244596112747,"score_spread":0.2239059565226361,"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."}}