{"id":"W2117244388","doi":"10.1109/icc.2005.1495076","title":"An adaptive scheduling algorithm for bluetooth ad-hoc networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Bluetooth and Wireless Communication Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Piconet; Bluetooth; Computer network; Scheduling (production processes); Wireless ad hoc network; Scatternet; Maximum throughput scheduling; Distributed computing; Dynamic priority scheduling; Algorithm; Wireless; Round-robin scheduling; Mathematical optimization; Quality of service; Mathematics","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":[0.0002526822,0.0001446402,0.0001557298,0.0001033249,0.0002280556,0.0001839075,0.002046661,0.0001386855,0.000009119019],"category_scores_gemma":[0.00001814436,0.0001286875,0.00006626509,0.0003103255,0.00006950561,0.0007025971,0.0002787584,0.0001880974,0.00002163159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003825206,"about_ca_system_score_gemma":0.00004610353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003662454,"about_ca_topic_score_gemma":0.00003064192,"domain_scores_codex":[0.998916,0.00003405281,0.0002201249,0.0003532125,0.0001248407,0.0003517343],"domain_scores_gemma":[0.9983557,0.0001272677,0.00008508976,0.001210684,0.0001276244,0.00009365651],"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":[0.000003100536,0.00004970886,0.000005126893,7.543982e-7,0.000007652149,2.264271e-7,0.00007145958,0.003829428,0.00002978333,0.0673364,0.0002418391,0.9284245],"study_design_scores_gemma":[0.0002766495,0.0002077609,0.00004630317,0.00000732836,0.000002693227,0.000002435256,0.0001541735,0.9715589,0.001849893,0.002357631,0.02334676,0.0001895253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009373764,0.002249854,0.9926789,0.001978016,0.0001017764,0.0002310064,0.000001778736,0.001130928,0.0006903163],"genre_scores_gemma":[0.2447284,0.0003060213,0.7540457,0.000639757,0.00007070816,0.00006543664,0.000003019665,0.00001002147,0.0001309494],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9677294,"threshold_uncertainty_score":0.5247725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02297641856061389,"score_gpt":0.2683557234745795,"score_spread":0.2453793049139656,"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."}}