{"id":"W2042685720","doi":"10.1007/s00453-010-9422-0","title":"Sleeping on the Job: Energy-Efficient and Robust Broadcast for Radio Networks","year":2010,"lang":"en","type":"article","venue":"Algorithmica","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; University of Victoria","funders":"","keywords":"Computer science; Node (physics); Broadcasting (networking); Computer network; Schedule; Theory of computation; Set (abstract data type); Binary logarithm; Radio networks; Discrete mathematics; Mathematics; Algorithm; Telecommunications; Wireless network; Wireless","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":[0.0004987977,0.0001964671,0.0001755039,0.00005073559,0.0003855688,0.000239698,0.0009051743,0.0001260733,0.0000148974],"category_scores_gemma":[0.00004497806,0.0001436451,0.0000805341,0.0002671751,0.0001134843,0.00009920576,0.0002739083,0.0003781534,0.000006988782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002187758,"about_ca_system_score_gemma":0.00002905929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000226237,"about_ca_topic_score_gemma":0.00001511018,"domain_scores_codex":[0.998509,0.00005641202,0.0002146035,0.0005240118,0.0002093842,0.0004865758],"domain_scores_gemma":[0.9981793,0.0006987167,0.00009170201,0.0008262109,0.00006758411,0.0001364886],"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":[0.000009232739,0.00005741375,0.00002027252,0.000003726441,0.00003214423,0.000007758599,0.0001507662,0.08538629,0.0001537518,0.3266127,0.009653824,0.5779122],"study_design_scores_gemma":[0.0002512844,0.00007525887,0.0002244602,0.00001524578,0.00000758974,0.00003059225,0.000006024133,0.9707367,0.000270876,0.0008224339,0.02737293,0.000186635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004719517,0.0002223176,0.9902206,0.001838672,0.001502396,0.0003271627,0.000002409927,0.0001354572,0.001031449],"genre_scores_gemma":[0.9024716,0.00004445155,0.09264495,0.002308807,0.001815321,0.0002627658,0.000004967318,0.00004705883,0.0004000663],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8977521,"threshold_uncertainty_score":0.5857679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01145844559915858,"score_gpt":0.209008588747466,"score_spread":0.1975501431483074,"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."}}