{"id":"W2053823116","doi":"10.1109/wcl.2012.051712.120156","title":"Prediction-Based Energy-Aware Relay Cooperation for Lifetime Maximization","year":2012,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Relay; Maximization; Power (physics); Channel (broadcasting); Channel state information; Energy (signal processing); Computational complexity theory; Mathematical optimization; Computer network; Algorithm; Wireless; Telecommunications; 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":[],"consensus_categories":[],"category_scores_codex":[0.0005566018,0.0002167989,0.0001984424,0.0002095225,0.00106952,0.0002095457,0.002291035,0.00009975227,0.0000137706],"category_scores_gemma":[0.00003874141,0.0002335131,0.0001085567,0.0007173308,0.0001370227,0.001040189,0.0002680952,0.0002164845,0.00002831622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001704006,"about_ca_system_score_gemma":0.00009450356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001069853,"about_ca_topic_score_gemma":0.00003103885,"domain_scores_codex":[0.9982023,0.0004583849,0.0004641066,0.0002821965,0.0002130967,0.0003799756],"domain_scores_gemma":[0.9957615,0.0005660751,0.0002039199,0.002976908,0.0003413571,0.0001502728],"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":[0.00007302417,0.001966766,0.008452742,0.00008592993,0.0002803354,8.734164e-7,0.004460233,0.04680065,0.07613458,0.4337322,0.1230339,0.3049788],"study_design_scores_gemma":[0.0005800869,0.00002948515,0.0004926194,0.00005150272,0.0000195005,0.000003400137,0.00001512727,0.9250678,0.003656281,0.00002549858,0.06977024,0.0002884069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002675589,0.0006021755,0.9761834,0.01890861,0.0005287555,0.000389808,0.00002193228,0.000408252,0.0002815061],"genre_scores_gemma":[0.9191566,0.0005715674,0.07342876,0.005607574,0.0001724712,0.0005918482,0.0003314134,0.00003109119,0.0001086488],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.916481,"threshold_uncertainty_score":0.9522388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04824519487529482,"score_gpt":0.2687440016354856,"score_spread":0.2204988067601908,"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."}}