{"id":"W2123545238","doi":"10.1109/tmc.2013.106","title":"An Optimization Framework for XOR-Assisted Cooperative Relaying in Cellular Networks","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Linear network coding; Cooperative diversity; Relay; Maximization; Optimization problem; Bipartite graph; Resource allocation; Coding (social sciences); Mathematical optimization; Channel (broadcasting); Computer network; Theoretical computer science; Power (physics); Algorithm; Mathematics; Fading","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":[0.0004130822,0.0002290343,0.0002525998,0.000215134,0.0007269559,0.0003817019,0.0007616685,0.0001551436,0.0000580528],"category_scores_gemma":[0.00001488194,0.0002409303,0.00009090886,0.0009785539,0.00004448223,0.0006965892,0.00001117854,0.0005332005,0.00001441896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00013686,"about_ca_system_score_gemma":0.00005088845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001362272,"about_ca_topic_score_gemma":0.00001697333,"domain_scores_codex":[0.9981398,0.0003319539,0.0004661379,0.0005255744,0.0001498657,0.0003866949],"domain_scores_gemma":[0.9980378,0.0007246634,0.0001295719,0.000753671,0.000233493,0.0001207591],"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":[0.000005418247,0.0001677394,0.00001336281,0.000004378379,0.00001061255,7.211492e-7,0.0006593944,0.8618472,0.0004194888,0.002044218,0.00001796035,0.1348095],"study_design_scores_gemma":[0.0004144539,0.0002137143,0.00008514051,0.000135151,0.000005590812,0.000002674184,0.000124142,0.9969605,0.00156918,0.0001609543,0.00005959486,0.0002688821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01060692,0.0001562513,0.9869474,0.0002262481,0.0005834939,0.001116437,0.000001226951,0.0002836831,0.0000783267],"genre_scores_gemma":[0.7408381,0.00008323679,0.2584299,0.0002788409,0.00005576852,0.0002650386,0.000005752925,0.00002132751,0.00002200114],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7302312,"threshold_uncertainty_score":0.9824853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02773428165406824,"score_gpt":0.2879395312478767,"score_spread":0.2602052495938085,"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."}}