{"id":"W2037785008","doi":"10.1155/2010/418934","title":"On the Complexity of Scheduling in Wireless Networks","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":139,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Army Research Office; Multidisciplinary University Research Initiative; National Science Foundation","keywords":"Computer science; Scheduling (production processes); Wireless network; Time complexity; Distributed computing; Wireless; Approximation algorithm; Computational complexity theory; Greedy algorithm; Mathematical optimization; Computer network; Algorithm; 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":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00194526,0.0002089003,0.0003147842,0.0001415029,0.0007919812,0.0002799215,0.00279921,0.0001189552,0.000008288282],"category_scores_gemma":[0.00002754046,0.0001559938,0.00009238734,0.0006925847,0.0005535292,0.000222458,0.0006790684,0.002522863,0.000002281346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003379983,"about_ca_system_score_gemma":0.00005005781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001323514,"about_ca_topic_score_gemma":0.0002041428,"domain_scores_codex":[0.997886,0.0005594743,0.0006164336,0.0002524481,0.000294903,0.0003907612],"domain_scores_gemma":[0.9955328,0.001873134,0.0004917834,0.001863224,0.0001117704,0.0001272849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002080171,0.0001706778,0.004044406,0.000003895202,0.00002502096,0.000007673389,0.0003178712,0.009545199,0.0002431612,0.8142272,0.00006908845,0.171325],"study_design_scores_gemma":[0.0003410547,0.00009434001,0.004580488,0.0003807814,0.000005587842,0.00006994793,0.00003565166,0.9815131,0.00004313949,0.01159053,0.001161204,0.0001841293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.838545,0.001406425,0.1473297,0.007869007,0.001286275,0.0003840275,8.852716e-7,0.00007170517,0.003106942],"genre_scores_gemma":[0.9910042,0.002632391,0.005569046,0.0004861394,0.0002634316,0.00001626986,0.000001657812,0.00001955255,0.000007254735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9719679,"threshold_uncertainty_score":0.9997783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05349021118341814,"score_gpt":0.2816610418362372,"score_spread":0.2281708306528191,"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."}}