{"id":"W1777436619","doi":"10.1002/wcm.2492","title":"CSMA/CA‐based medium access control for indoor millimeter wave networks","year":2014,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Computer network; Throughput; Node (physics); Network packet; Transmission (telecommunications); Narrowband; Bandwidth (computing); Random access; Network congestion; Carrier sense multiple access with collision avoidance; Exponential backoff; Access control; Wireless; 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":[0.0007298584,0.0004592135,0.0003431294,0.0005254889,0.000732264,0.0008329314,0.001175835,0.0005244211,0.001500791],"category_scores_gemma":[0.001942199,0.0001532874,0.0002579029,0.000496337,0.0006911864,0.0005352724,0.0004481853,0.0008489839,0.0002155892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008577401,"about_ca_system_score_gemma":0.001305651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01034856,"about_ca_topic_score_gemma":0.008064871,"domain_scores_codex":[0.9995122,0.00009923553,0.00002515778,0.0001063088,0.0001811307,0.00007595247],"domain_scores_gemma":[0.9991696,0.0003198385,0.0001235185,0.0000775126,0.0002662752,0.00004328758],"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":[0.0004885829,0.0002208559,0.001700768,0.0002337763,0.0001228407,0.000270467,0.0001825228,0.7169309,0.03787602,0.04568354,0.00622318,0.1900665],"study_design_scores_gemma":[0.00001905285,0.00005478198,0.0001386019,0.000005992089,0.00001907497,0.00003008807,0.000008269209,0.9932762,0.003063234,0.001609601,0.001766233,0.000008937967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04913757,0.001736365,0.9413667,0.000251158,0.000356412,0.0001207655,0.0000516282,0.0009560729,0.006023366],"genre_scores_gemma":[0.9516401,0.0005480249,0.04447845,0.00009154083,0.00009405063,0.0001196087,0.00003717893,0.00001455644,0.002976573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01034856,"threshold_uncertainty_score":0.02057666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02976600768038707,"score_gpt":0.2656846839258581,"score_spread":0.2359186762454711,"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."}}