{"id":"W2185139478","doi":"10.1109/wcsp.2015.7341142","title":"Resource allocation for two-hop communication with energy harvesting constraints","year":2015,"lang":"en","type":"article","venue":"","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Relay; Scheduling (production processes); Hop (telecommunications); Computer network; Maximization; Fading; Throughput; Communications system; Dynamic priority scheduling; Distributed computing; Channel (broadcasting); Mathematical optimization; Wireless; Power (physics); Telecommunications; Quality of service","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":[0.0008916138,0.0008071001,0.0009428216,0.0003837069,0.0004886914,0.00120974,0.001106951,0.0008228312,0.002706269],"category_scores_gemma":[0.001889947,0.0003782124,0.0003665959,0.00099716,0.0006329523,0.001466549,0.001031047,0.0007425895,0.0003356234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009407421,"about_ca_system_score_gemma":0.0008711615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001613578,"about_ca_topic_score_gemma":0.001538664,"domain_scores_codex":[0.9994004,0.0002320276,0.00002301819,0.000119391,0.0001097566,0.0001154311],"domain_scores_gemma":[0.9991278,0.000629603,0.00008157791,0.00005089786,0.00007185953,0.00003830652],"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":[0.00007807254,0.000076044,0.0002368291,0.0001547018,0.00004088624,0.0002214403,0.0000887722,0.9357152,0.003612529,0.04069636,0.001004727,0.01807446],"study_design_scores_gemma":[0.00001368456,0.00003648439,0.00009484826,0.000007076985,0.000007044011,0.00004155668,0.00002742862,0.9871647,0.0004511105,0.01158289,0.0005632292,0.000009823762],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03482342,0.0007235996,0.9577138,0.0002931758,0.00005707703,0.00008995274,0.00009202867,0.0000860988,0.006120786],"genre_scores_gemma":[0.9303035,0.0006118153,0.06370408,0.0001176673,0.00004826332,0.0002347773,0.00006592675,0.00003492359,0.004879094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002706269,"threshold_uncertainty_score":0.009053349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02298322650759086,"score_gpt":0.2271782857606312,"score_spread":0.2041950592530404,"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."}}