{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005080805,0.0001963665,0.0002854945,0.0001091868,0.0003989106,0.0001528933,0.0004798737,0.0001068145,0.000009527576],"category_scores_gemma":[0.00002465868,0.0001978556,0.00008326996,0.0001305967,0.00008189707,0.0001071958,0.0001848242,0.0002368082,0.000002448286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002964911,"about_ca_system_score_gemma":0.00001601771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001227296,"about_ca_topic_score_gemma":0.00001499833,"domain_scores_codex":[0.9988844,0.0001017544,0.0004096573,0.0002118755,0.00008936776,0.0003029251],"domain_scores_gemma":[0.9981319,0.0007309935,0.00009099884,0.0007944504,0.0001402683,0.0001113904],"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":[0.00002286546,0.0001006322,0.0007965212,0.0002380741,0.0001334477,3.382234e-7,0.0004833616,0.5334023,0.00693487,0.0005573923,0.0004769143,0.4568533],"study_design_scores_gemma":[0.0009564993,0.00004570655,0.0001325591,0.00008390793,0.00003473099,0.000002142681,0.00003785691,0.9914272,0.001439302,0.00007712457,0.005527688,0.0002352092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09116151,0.001003331,0.9063157,0.0001328611,0.000190565,0.000595117,0.00001408792,0.0002161586,0.0003706189],"genre_scores_gemma":[0.9833571,0.0002467952,0.01549899,0.0003738157,0.0001268331,0.0002315882,0.0001059497,0.00004984207,0.000009105055],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8921956,"threshold_uncertainty_score":0.8068318,"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."}}