{"id":"W4388079656","doi":"10.1109/jiot.2023.3328733","title":"Contention With Collision Detection in Wireless Full-Duplex Networks","year":2023,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"National Key Research and Development Program of China","keywords":"Computer science; Collision; Overhead (engineering); Computer network; Node (physics); Duplex (building); Wireless network; Hidden node problem; Wireless; Channel (broadcasting); Transmission (telecommunications); Collision detection; Wi-Fi array; Telecommunications; Computer security; Engineering","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":[0.002251852,0.0005112328,0.0008309453,0.000997628,0.0009416819,0.00175182,0.001645402,0.00103288,0.001023303],"category_scores_gemma":[0.007599167,0.000690005,0.0004729723,0.001435426,0.001787927,0.002292604,0.0009863122,0.001018389,0.0001838859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001775424,"about_ca_system_score_gemma":0.001968941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003660459,"about_ca_topic_score_gemma":0.001913452,"domain_scores_codex":[0.9972305,0.000939326,0.0001040458,0.0003631199,0.001153284,0.0002097762],"domain_scores_gemma":[0.9963146,0.002465805,0.0002988178,0.0003186339,0.0005327536,0.00006937046],"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":[0.000163228,0.0001136316,0.002215454,0.0004030011,0.00011482,0.0004816879,0.0004054084,0.6237041,0.01023132,0.2609994,0.002633881,0.09853411],"study_design_scores_gemma":[0.00002042142,0.00006950249,0.0002272217,0.0000230382,0.00002282458,0.0002081253,0.00004583345,0.9599398,0.002229663,0.03410723,0.003075324,0.00003098358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01562214,0.003402652,0.9762185,0.0002616303,0.0001603047,0.00008890493,0.00003568201,0.0002168629,0.003993435],"genre_scores_gemma":[0.8946801,0.004080898,0.09688812,0.0001910845,0.0002161681,0.0002521469,0.00005556328,0.00005331303,0.003582504],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003660459,"threshold_uncertainty_score":0.0128817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01393474523987245,"score_gpt":0.2242476090840835,"score_spread":0.2103128638442111,"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."}}