{"id":"W2104242807","doi":"10.1109/twc.2012.031212.101702","title":"Resource Allocation via Linear Programming for Fractional Cooperation","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Relay; Mathematical optimization; Resource allocation; Linear programming; Optimization problem; Demodulation; Low-density parity-check code; Decoding methods; Computer network; Telecommunications; Algorithm; Mathematics; Channel (broadcasting)","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.000663698,0.0002149808,0.0001879216,0.0002195847,0.001780287,0.0001434565,0.001634177,0.0001218866,0.00002452584],"category_scores_gemma":[0.00001973606,0.0002321848,0.0001395924,0.0007650757,0.000124753,0.001115418,0.00002716692,0.0004474818,0.00008362982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001711901,"about_ca_system_score_gemma":0.00008986852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008500877,"about_ca_topic_score_gemma":0.00006820739,"domain_scores_codex":[0.9983098,0.0003424717,0.0004420838,0.0002863099,0.0002388394,0.0003805053],"domain_scores_gemma":[0.9962081,0.0007184337,0.0001617379,0.002350326,0.0003891834,0.000172213],"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":[0.00003410139,0.001662659,0.00003534262,0.00001918196,0.0001043959,9.249684e-8,0.002129902,0.009135455,0.006264708,0.1221086,0.0007775648,0.8577279],"study_design_scores_gemma":[0.0007494643,0.0001353158,0.0001323994,0.00006519546,0.00004472323,0.00001808054,0.0001056826,0.7385303,0.01229523,0.0001378535,0.2472853,0.0005004866],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006225564,0.0003526119,0.9908791,0.00612532,0.0003406765,0.0007524144,0.00001051572,0.000391838,0.0005250039],"genre_scores_gemma":[0.8806766,0.000534056,0.1167028,0.0005902335,0.00009582981,0.0009454949,0.00006730507,0.00002757766,0.0003601053],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8800541,"threshold_uncertainty_score":0.9995193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06050846789202001,"score_gpt":0.3150134039708821,"score_spread":0.254504936078862,"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."}}