{"id":"W1999547539","doi":"10.1145/2425248.2425278","title":"Network criticality in vehicular networks","year":2012,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Criticality; Centrality; Computer science; Robustness (evolution); Cluster analysis; Network science; Graph; Complex network; Metric (unit); Theoretical computer science; Distributed computing; Data mining; Computer network; Mathematics; Artificial intelligence; Engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007678332,0.00022012,0.0004964239,0.0001753862,0.0001242137,0.00003355808,0.0004328522,0.0000570751,0.001917146],"category_scores_gemma":[0.0004159076,0.000206118,0.0001623526,0.0034596,0.0000355103,0.0004380819,0.0001970177,0.0003407283,0.00009516786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001263927,"about_ca_system_score_gemma":0.00005459338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002183859,"about_ca_topic_score_gemma":0.000001241654,"domain_scores_codex":[0.9972896,0.0004307998,0.0007277301,0.0002724151,0.0006524569,0.0006270148],"domain_scores_gemma":[0.9981132,0.000348713,0.0002135395,0.0008932499,0.0003014903,0.0001298314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002195527,0.0001235986,0.638414,0.0001469132,0.00002970454,1.039849e-7,0.00001133562,0.006337954,7.243837e-7,0.003017716,0.00985722,0.3420585],"study_design_scores_gemma":[0.0007335596,0.00007382993,0.4271893,0.003052378,0.0009707749,0.000002151195,0.00001729809,0.4861021,0.0000378985,0.006600851,0.07417907,0.001040763],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2739725,0.6213408,0.07431181,0.001577884,0.001050754,0.00475356,0.000007085167,0.0002757281,0.02270986],"genre_scores_gemma":[0.9851675,0.01002636,0.002577609,0.0008645884,0.0008853104,0.0003192977,0.0001185339,0.00001974321,0.00002105681],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.711195,"threshold_uncertainty_score":0.9989952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0660193517817655,"score_gpt":0.3624161608344549,"score_spread":0.2963968090526894,"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."}}