{"id":"W1968098382","doi":"10.1002/dac.1386","title":"Ubiquitous computing for communications and broadcasting","year":2012,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Ubiquitous computing; Broadcasting (networking); Presentation (obstetrics); Focus (optics); Wireless sensor network; Quality (philosophy); Data science; Multimedia; Telecommunications; Human–computer interaction; Computer security; Computer network","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":[0.0006103884,0.00008487849,0.0001548413,0.0001344828,0.00009202701,0.00007594609,0.000640138,0.00004690058,0.000001261393],"category_scores_gemma":[0.00007613638,0.00008843158,0.00004285043,0.00007676789,0.00004506267,0.0005035283,0.0001093039,0.0001560078,0.000001489239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001046061,"about_ca_system_score_gemma":0.00001093888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003030931,"about_ca_topic_score_gemma":0.000001010381,"domain_scores_codex":[0.999038,0.00007630551,0.0005443932,0.00003688339,0.0001797861,0.0001246666],"domain_scores_gemma":[0.9982135,0.0005302579,0.0003471658,0.0003021285,0.0005414725,0.00006544753],"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":[0.00003240782,0.00008401443,0.009937253,0.00003456056,0.0003506648,4.848816e-7,0.002915045,0.8995532,0.001332771,0.01668379,0.001252563,0.06782321],"study_design_scores_gemma":[0.0006389554,0.00002379563,0.001016631,0.000325549,0.00002635425,0.0001826807,0.000750745,0.9447165,0.0001495342,0.0001508366,0.0518658,0.0001526825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04581317,0.0358866,0.9143425,0.0003188678,0.001804622,0.0002448293,0.00001066897,0.00009071776,0.001488067],"genre_scores_gemma":[0.9511068,0.002677043,0.0457288,0.00002188272,0.0004036571,0.00000845224,0.00001859362,0.00002323877,0.00001147161],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9052937,"threshold_uncertainty_score":0.3606135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02736784115071575,"score_gpt":0.3015368478395857,"score_spread":0.27416900668887,"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."}}