{"id":"W2146968416","doi":"10.1109/rawcon.2003.1227934","title":"Reducing collisions between bluetoioth piconets by orthogonal hop set partitioning","year":2004,"lang":"en","type":"article","venue":"","topic":"Bluetooth and Wireless Communication Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Piconet; Hop (telecommunications); Bluetooth; Computer science; Computer network; Set (abstract data type); Algorithm; 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":[0.0004435623,0.0005553527,0.0004751493,0.0005258118,0.0006818644,0.0004650085,0.0008122977,0.000316452,0.0008731385],"category_scores_gemma":[0.001524319,0.0002487663,0.000247434,0.000353971,0.0004631094,0.0007865285,0.001133638,0.0004467732,0.000281595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002851876,"about_ca_system_score_gemma":0.0003538698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003876195,"about_ca_topic_score_gemma":0.0007191696,"domain_scores_codex":[0.9994779,0.0001356111,0.00003399469,0.00007744533,0.0001922781,0.00008273864],"domain_scores_gemma":[0.9988562,0.0004939425,0.0001722031,0.0002678671,0.0001490939,0.00006069309],"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":[0.001592786,0.0003737944,0.00621098,0.0003009957,0.0001624616,0.0003876104,0.0005939782,0.09917136,0.3076698,0.02408549,0.001870834,0.55758],"study_design_scores_gemma":[0.0003187354,0.00269088,0.005554868,0.00007201577,0.0002514434,0.002026867,0.0004096119,0.6534981,0.2956501,0.01756534,0.0218359,0.0001260781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2246859,0.0005919236,0.7701694,0.0001355906,0.00007856193,0.0001067315,0.00004335488,0.0004118267,0.003776728],"genre_scores_gemma":[0.7807677,0.0002522044,0.2162906,0.00008894104,0.00007137936,0.0001178871,0.0001150677,0.00004053954,0.002255661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008731385,"threshold_uncertainty_score":0.002920985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02946719735143463,"score_gpt":0.2693003038839772,"score_spread":0.2398331065325426,"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."}}