{"id":"W2043577274","doi":"10.1002/wcm.443","title":"Forward focus: using routing information to improve medium access control in ad hoc networks","year":2006,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Computer network; Packet forwarding; Wireless ad hoc network; Network packet; Optimized Link State Routing Protocol; Routing protocol; Routing (electronic design automation); Distributed computing; Telecommunications; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001500275,0.0006970812,0.0004241722,0.0009093319,0.0003495419,0.0005514033,0.00111683,0.0007408797,0.001274587],"category_scores_gemma":[0.004187701,0.0002376047,0.0002068177,0.0003440167,0.0003931391,0.001691455,0.0008931043,0.0004878299,0.0002649743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002739948,"about_ca_system_score_gemma":0.0003772151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008866257,"about_ca_topic_score_gemma":0.0008394843,"domain_scores_codex":[0.9995691,0.0001724832,0.00001633838,0.00005193267,0.0001481993,0.00004193301],"domain_scores_gemma":[0.9982299,0.001024833,0.0002045404,0.0001855594,0.000291343,0.00006384211],"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":[0.000547232,0.0006476695,0.003738096,0.0003445886,0.0001432454,0.0004852962,0.0005135842,0.1992869,0.1059928,0.03052426,0.005597387,0.652179],"study_design_scores_gemma":[0.000183543,0.001260859,0.002570251,0.0000826559,0.0001858571,0.0006294969,0.0001116091,0.9077379,0.04917701,0.02672703,0.01125755,0.00007622842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1933231,0.003697006,0.7906647,0.0009749066,0.0003412807,0.00021869,0.00005030075,0.002507826,0.008222234],"genre_scores_gemma":[0.8379758,0.0009927343,0.1575122,0.0002460508,0.0001586012,0.0001124834,0.0000811689,0.00006699785,0.002853925],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001500275,"threshold_uncertainty_score":0.007934332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01460295727876204,"score_gpt":0.2856872982169892,"score_spread":0.2710843409382271,"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."}}