{"id":"W1993970997","doi":"10.5555/1460047.1460077","title":"Network selection with imprecise information in heterogeneous all-IP wireless systems","year":2007,"lang":"en","type":"article","venue":"International Wireless Internet Conference","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Heterogeneous network; Selection (genetic algorithm); Wireless network; Quality of service; Process (computing); Heterogeneous wireless network; Computer network; Distributed computing; Wireless; Machine learning; Telecommunications","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":[0.009408349,0.0008046171,0.001336651,0.002154693,0.001159506,0.002695515,0.001141421,0.0008510663,0.0005860961],"category_scores_gemma":[0.02442322,0.0005785184,0.0008106437,0.001791384,0.001580869,0.003596168,0.001485767,0.001163792,0.00007657909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001480594,"about_ca_system_score_gemma":0.0007650032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002009055,"about_ca_topic_score_gemma":0.001542452,"domain_scores_codex":[0.9927953,0.003312881,0.0004007859,0.0006478812,0.00250944,0.0003338139],"domain_scores_gemma":[0.9825934,0.01366311,0.001662387,0.0006948883,0.001075951,0.0003102762],"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":[0.0002293119,0.00005560124,0.004125409,0.0001069674,0.0001351088,0.0003808253,0.0003060446,0.9157144,0.002258873,0.02930038,0.0002341538,0.04715286],"study_design_scores_gemma":[0.00001344204,0.00006041309,0.001244411,0.00002119965,0.00003608036,0.00006943617,0.0001160987,0.9601577,0.002039225,0.03587748,0.0003361198,0.00002832309],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09628866,0.0004031235,0.9019891,0.0002444792,0.00001411741,0.00004107904,0.00003830628,0.00006992,0.0009112003],"genre_scores_gemma":[0.9215367,0.0002193111,0.07782326,0.00002954748,0.00002338118,0.00003418467,0.00004139036,0.00001500267,0.0002771641],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009408349,"threshold_uncertainty_score":0.04975671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01099726789199656,"score_gpt":0.223555846095902,"score_spread":0.2125585782039054,"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."}}