{"id":"W2123467153","doi":"10.1109/icc.2007.796","title":"Energy-Efficient Multi-Hop Scheduling for Multi-Rate 802.15.3 WPANs","year":2007,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Scheduling (production processes); Hop (telecommunications); Computer network; Energy consumption; Decoding methods; Efficient energy use; Interference (communication); Channel (broadcasting); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006615673,0.0004394341,0.0004855845,0.0003708406,0.000536763,0.0004339034,0.0009233619,0.0002675017,0.00079155],"category_scores_gemma":[0.001064528,0.0001844828,0.0003383139,0.0004487769,0.0003118452,0.000536418,0.000501294,0.0004354896,0.0002379132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005584315,"about_ca_system_score_gemma":0.0006462326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001175942,"about_ca_topic_score_gemma":0.002242752,"domain_scores_codex":[0.9996698,0.00007811406,0.00002615889,0.00003636114,0.000141762,0.00004769973],"domain_scores_gemma":[0.9996309,0.0001045424,0.00007592492,0.00007749959,0.00008515271,0.00002591432],"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":[0.0003146221,0.0001635928,0.001061365,0.0002079666,0.00008671314,0.0002820539,0.0002171784,0.6093153,0.06762862,0.05722648,0.00317874,0.2603173],"study_design_scores_gemma":[0.00002678968,0.0001100522,0.0003904466,0.00001023203,0.00002045985,0.0001367125,0.00002166463,0.9693707,0.01639454,0.009933731,0.003561921,0.00002273166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0323821,0.0008692982,0.9640475,0.0001009498,0.0001237789,0.00005463599,0.00003824204,0.0002505812,0.002132931],"genre_scores_gemma":[0.7096989,0.0007601292,0.2874243,0.00006155412,0.00006700595,0.000113531,0.0000673121,0.00006570811,0.001741507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001175942,"threshold_uncertainty_score":0.004051745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05229378713474699,"score_gpt":0.3152660737050187,"score_spread":0.2629722865702717,"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."}}