{"id":"W2141453446","doi":"10.1007/s11036-010-0241-y","title":"DFMAC: DTN-Friendly Medium Access Control for Wireless Local Area Networks Supporting Voice/Data Services","year":2010,"lang":"en","type":"article","venue":"Mobile Networks and Applications","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Roaming; Computer network; Computer science; Node (physics); Access control; Wi-Fi; Wireless; Local area network; Wireless network; Delay-tolerant networking; Scheme (mathematics); Wireless ad hoc network; Telecommunications; Vehicular ad hoc 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007810564,0.0006176726,0.0006005871,0.0008947141,0.0009623835,0.001042432,0.001099524,0.0005872737,0.003984879],"category_scores_gemma":[0.001956498,0.0001934683,0.0002121637,0.0004892463,0.000470082,0.000683922,0.0009747564,0.001049154,0.001047646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009374111,"about_ca_system_score_gemma":0.001059745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005227703,"about_ca_topic_score_gemma":0.01132181,"domain_scores_codex":[0.9995442,0.00005749212,0.00002880125,0.00006070467,0.0001970797,0.0001115987],"domain_scores_gemma":[0.999253,0.0001321875,0.0000616235,0.0001340295,0.0003423489,0.00007682784],"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":[0.001213985,0.0003460688,0.001501005,0.0004488871,0.00008469675,0.0006265636,0.0003339398,0.0314393,0.109951,0.07024403,0.09328077,0.6905297],"study_design_scores_gemma":[0.0001706336,0.0004578983,0.001120366,0.00006838301,0.0001023528,0.000828504,0.00006761192,0.746828,0.05610111,0.01985696,0.1742963,0.0001019652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02399972,0.00214918,0.941349,0.0006000114,0.001313647,0.0005181351,0.0008541446,0.01241446,0.01680168],"genre_scores_gemma":[0.7162337,0.001051194,0.2489101,0.001325493,0.0005957075,0.0005968553,0.001704842,0.0004874198,0.02909477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005227703,"threshold_uncertainty_score":0.0133307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01514643345955427,"score_gpt":0.2835256832422676,"score_spread":0.2683792497827134,"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."}}