{"id":"W4229715808","doi":"10.1002/wcm.525","title":"An efficient MAC protocol for cooperative diversity in mobile ad hoc networks","year":2007,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Computer science; Computer network; Cooperative diversity; Relay; Throughput; Fading; Blocking (statistics); Wireless ad hoc network; Mobile ad hoc network; Protocol (science); Diversity gain; Channel (broadcasting); Wireless; Telecommunications; Network packet","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001661769,0.0002126481,0.0002738,0.0001711535,0.001784326,0.0002077698,0.002290812,0.00009331636,0.000003975797],"category_scores_gemma":[0.0000167052,0.0002157618,0.00005720359,0.0006887253,0.0001950063,0.0002498351,0.003467869,0.0003658884,0.000001358595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001120857,"about_ca_system_score_gemma":0.00005733715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007235867,"about_ca_topic_score_gemma":0.0002573726,"domain_scores_codex":[0.9981802,0.0003202256,0.0004908491,0.0004465782,0.0001410892,0.0004210179],"domain_scores_gemma":[0.9966888,0.0007416643,0.0001886798,0.001909951,0.0003194888,0.0001513679],"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":[0.00003609631,0.0006289009,0.001692141,0.00002168664,0.00001410927,0.000001434536,0.006892356,0.03499764,0.0002169135,0.01635591,0.00004526558,0.9390975],"study_design_scores_gemma":[0.001132579,0.0002887826,0.002054172,0.0001148806,0.000003434034,0.000004561176,0.0005845011,0.9709098,0.00008720779,0.00003735249,0.02450646,0.0002762286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07540762,0.002056586,0.8777766,0.0001152758,0.00006995491,0.04402756,0.000002997135,0.0002022573,0.0003411107],"genre_scores_gemma":[0.9416878,0.0006489804,0.0311716,0.0001672593,0.00002976856,0.0262456,0.00001735106,0.00001513804,0.00001647274],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9388213,"threshold_uncertainty_score":0.9995152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05114150699580787,"score_gpt":0.3517409192006437,"score_spread":0.3005994122048358,"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."}}