{"id":"W2116946664","doi":"10.1109/lcomm.2007.061291","title":"Traffic models for medical wireless sensor networks","year":2007,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Wireless Body Area Networks","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Wireless sensor network; Computer science; Computer network; Wireless; Key distribution in wireless sensor networks; Wireless network; 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":[0.0006540907,0.0001976032,0.0002208335,0.0001155967,0.0002197297,0.00003854225,0.001218053,0.000211358,0.000009989025],"category_scores_gemma":[0.00001609977,0.000223045,0.0001145888,0.0002771907,0.0001981258,0.0001517021,0.00006910133,0.0005142003,0.00001289003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000115804,"about_ca_system_score_gemma":0.00001677868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006591132,"about_ca_topic_score_gemma":0.0001690891,"domain_scores_codex":[0.9986136,0.00004845699,0.0004284779,0.0001734671,0.0002272975,0.0005087093],"domain_scores_gemma":[0.9973783,0.000848941,0.00004525098,0.001489012,0.00005164063,0.0001868733],"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":[0.000008604764,0.00003257781,0.00001556356,0.00001723801,0.00005744403,0.000004025391,0.0001988095,0.9540997,0.0006845328,0.0006107314,0.01726647,0.02700437],"study_design_scores_gemma":[0.0003628731,0.00000665965,0.00005416115,0.0000551698,0.000020542,0.00001310575,0.00004432602,0.9936231,0.000139657,0.00002550302,0.005408844,0.0002460673],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1519967,0.0005932126,0.841848,0.003004063,0.0005716567,0.0003621306,0.00000842784,0.0006930082,0.0009228358],"genre_scores_gemma":[0.9855186,0.0004027377,0.01210363,0.001321712,0.0003710634,0.0001087753,0.00006866123,0.00008618722,0.00001858481],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.833522,"threshold_uncertainty_score":0.9095512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02251400689620991,"score_gpt":0.2547415714723639,"score_spread":0.232227564576154,"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."}}