{"id":"W2963406336","doi":"10.19026/rjaset.7.229","title":"Analyzing Delay in Wireless Multi-hop Heterogeneous Body Area Networks","year":2014,"lang":"en","type":"article","venue":"Research Journal of Applied Sciences Engineering and Technology","topic":"Wireless Body Area Networks","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer network; Body area network; UMTS frequency bands; Computer science; WiMAX; Wireless sensor network; Wireless network; Wi-Fi; Wireless; Wireless WAN; Key distribution in wireless sensor networks; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002314294,0.000175507,0.0003619491,0.001786003,0.0001273993,0.00008005392,0.0005798999,0.0002409931,0.000002663989],"category_scores_gemma":[0.0001156328,0.0001595896,0.00003477471,0.002033507,0.0003540688,0.0001089832,0.000124943,0.001238768,0.000001468153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009356144,"about_ca_system_score_gemma":0.00002967013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002944089,"about_ca_topic_score_gemma":0.00001453961,"domain_scores_codex":[0.9982316,0.00002737651,0.0004176277,0.0002289118,0.0003338541,0.0007605573],"domain_scores_gemma":[0.9992214,0.0002763383,0.00005774233,0.0001818229,0.0001183702,0.000144286],"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":[0.000006846075,0.00001673222,0.0008381621,0.0000256053,0.00002377474,0.00005021637,0.00004321291,0.9705279,0.01107631,0.002378511,0.00003040194,0.01498225],"study_design_scores_gemma":[0.0003513439,0.00009924803,0.0001337678,0.0001184296,0.000004015136,0.0001458849,0.00008315429,0.9947856,0.003639584,0.0002619395,0.0002191993,0.0001578311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8940492,0.001323498,0.103907,0.00006720721,0.0001747938,0.0001010181,3.572209e-7,0.0001391566,0.0002377475],"genre_scores_gemma":[0.995873,0.0006146158,0.003353752,0.000002777956,0.0001154813,0.00001167464,3.163938e-7,0.00002652962,0.000001873179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1018238,"threshold_uncertainty_score":0.6507877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01833780066324024,"score_gpt":0.2649083019131143,"score_spread":0.246570501249874,"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."}}