{"id":"W2083626523","doi":"10.1109/infocom.2014.6848116","title":"GeoMob: A mobility-aware geocast scheme in metropolitans via taxicabs and buses","year":2014,"lang":"en","type":"article","venue":"","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Geocast; Computer science; Scalability; Computer network; Multicast; Scheme (mathematics); TRACE (psycholinguistics); Distributed computing; Routing protocol; Routing (electronic design automation); Database; Optimized Link State 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004523802,0.0001630609,0.0002481809,0.0001058442,0.00008538062,0.0001117853,0.0004069414,0.00009139969,0.00006907108],"category_scores_gemma":[0.0000127002,0.0001366518,0.00004047479,0.0003048904,0.0001110071,0.0002953311,0.0002735243,0.0001639707,0.00003825817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000320935,"about_ca_system_score_gemma":0.00004022773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005032613,"about_ca_topic_score_gemma":0.0002039595,"domain_scores_codex":[0.9985899,0.00007267304,0.0002758313,0.0004670277,0.000199298,0.0003952441],"domain_scores_gemma":[0.9989631,0.000182444,0.00005152358,0.0005558591,0.00005418814,0.0001928421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003826906,0.000635927,0.07017101,0.0001182685,0.00005253971,0.0001333187,0.0008798077,0.00007197358,0.0002179609,0.4213416,0.00523437,0.501105],"study_design_scores_gemma":[0.0003816031,0.0001091832,0.003263741,0.00001863179,0.000003740595,0.00003371646,0.00007530913,0.9803812,0.00004627032,0.01161105,0.003843058,0.0002324778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04344375,0.00009579576,0.9463552,0.0005941467,0.0001349935,0.0001212547,0.000002340137,0.000129291,0.00912319],"genre_scores_gemma":[0.9749082,0.00001887335,0.0237148,0.0007669715,0.00007023323,0.00001230726,0.000002577339,0.000007847047,0.0004981607],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9803092,"threshold_uncertainty_score":0.55725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008655094280764433,"score_gpt":0.2133067178754876,"score_spread":0.2046516235947231,"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."}}