{"id":"W2006868690","doi":"10.1109/icc.2012.6364718","title":"Robust clustering for connected vehicles using local network criticality","year":2012,"lang":"en","type":"article","venue":"","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Criticality; Computer science; Cluster analysis; Wireless ad hoc network; Robustness (evolution); Distributed computing; Computer network; Wireless sensor network; Network topology; Topology control; Wireless network; Topology (electrical circuits); Wireless; Key distribution in wireless sensor networks; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003835964,0.0002078263,0.0002624428,0.00002925118,0.0001188182,0.00004690059,0.000122542,0.0001583411,0.0001062144],"category_scores_gemma":[0.00003709214,0.0002124503,0.00009572902,0.0001652616,0.00005656293,0.0002469204,0.00006141944,0.0001741803,0.00002259811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001358207,"about_ca_system_score_gemma":0.0000106546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001820262,"about_ca_topic_score_gemma":0.00007174869,"domain_scores_codex":[0.9983813,0.0000368757,0.0002827108,0.0001671099,0.0001282665,0.001003809],"domain_scores_gemma":[0.9992294,0.0002083915,0.00001637401,0.0002429425,0.00005270803,0.0002501591],"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":[0.000009738711,0.0000185269,0.0006313596,0.00008377673,0.00004500876,0.000001475058,0.00002915412,0.9932584,0.0004570518,0.001412405,0.002367296,0.001685857],"study_design_scores_gemma":[0.0003181933,0.00001357021,0.0006274485,0.00004299143,0.00004310526,0.00002388796,0.00005072034,0.9940413,0.000721244,0.000148424,0.00367635,0.0002928122],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1269828,0.0006775885,0.8695295,0.00003008534,0.0007566185,0.0002696414,0.000005311091,0.0005878738,0.001160651],"genre_scores_gemma":[0.9443981,0.000006796406,0.05408416,0.0001386799,0.001231457,0.00002185959,0.00001531591,0.00007375103,0.00002987753],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8174154,"threshold_uncertainty_score":0.866347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04570680671235021,"score_gpt":0.2484361694298724,"score_spread":0.2027293627175222,"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."}}