{"id":"W1997000105","doi":"10.1109/wicom.2006.330","title":"Adaptive MAC Scheduling Using Channel State Diversity for Wireless Networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Computer network; Scheduling (production processes); Wireless; Wireless network; Multicast; Throughput; Real-time computing; Telecommunications; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002922754,0.0001644648,0.0001941474,0.00005277256,0.0005812636,0.0001662251,0.0005977189,0.00007621891,0.000005046276],"category_scores_gemma":[0.000001958965,0.0001527595,0.00009527585,0.000279052,0.00003525768,0.0004499748,0.0007052373,0.0001181174,0.000003191625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005487001,"about_ca_system_score_gemma":0.00003688453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005565222,"about_ca_topic_score_gemma":0.00009027641,"domain_scores_codex":[0.9987147,0.00004063075,0.0001941421,0.00039367,0.0001741209,0.0004827141],"domain_scores_gemma":[0.9993119,0.0001037781,0.0001108623,0.0002751186,0.0001198677,0.00007849184],"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":[0.00004442519,0.00005010794,0.0006878805,0.00001314437,0.00002049876,0.000008735788,0.0001128084,0.9486251,0.00003458216,0.03473579,0.0006295128,0.01503737],"study_design_scores_gemma":[0.0004404521,0.00005925002,0.0003309541,0.0000349382,0.000005003259,0.000002557352,0.00001375011,0.9885491,0.0002835097,0.009880304,0.0001756745,0.0002245111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01260227,0.00005033493,0.9838096,0.0000885446,0.0002436518,0.002599617,0.000003622318,0.0001692312,0.0004330915],"genre_scores_gemma":[0.8896889,0.000003391483,0.1092379,0.0001918746,0.0003412297,0.000252351,0.000002967568,0.00001288618,0.0002685096],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8770866,"threshold_uncertainty_score":0.6229351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03722533657495033,"score_gpt":0.2530966606322575,"score_spread":0.2158713240573072,"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."}}