{"id":"W2762753333","doi":"10.1109/lcomm.2017.2759106","title":"Two-Way Relay Selection for Millimeter Wave Networks","year":2017,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Relay; Computer science; Selection (genetic algorithm); Computer network; Extremely high frequency; Telecommunications; Physics; Artificial intelligence; Power (physics)","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":[0.0002419934,0.000143279,0.0001370288,0.00008770137,0.0008209476,0.0001603,0.00064624,0.00006742778,0.00001237017],"category_scores_gemma":[0.00003291531,0.0001561189,0.0001019222,0.00005299769,0.00008230903,0.0002313702,0.00006925762,0.00025249,0.00002337449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007744985,"about_ca_system_score_gemma":0.000005957962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003629485,"about_ca_topic_score_gemma":0.0001025647,"domain_scores_codex":[0.9992428,0.00004271767,0.0002506298,0.0001500693,0.00007588389,0.0002378477],"domain_scores_gemma":[0.9980137,0.0001058896,0.00008619198,0.001663071,0.00007174869,0.00005937946],"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":[0.00001722757,0.00004539337,0.00038506,0.00004489168,0.0002193998,5.87753e-7,0.0004533303,0.5793461,0.3641967,0.0002885326,0.02175139,0.0332513],"study_design_scores_gemma":[0.0004012934,0.00001119753,0.0001666155,0.00002798883,0.00003607806,0.000005062358,0.00000919932,0.9750948,0.01553979,0.00004947163,0.008448537,0.0002099558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08012393,0.0002544842,0.9147108,0.002352083,0.0005777467,0.0003390076,0.000008361025,0.0002403426,0.00139331],"genre_scores_gemma":[0.9422144,0.0002642223,0.0562079,0.0007897802,0.0001718442,0.0001715848,0.00004031516,0.00004818631,0.00009178917],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8620905,"threshold_uncertainty_score":0.6366345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06177513743133975,"score_gpt":0.2819548021884453,"score_spread":0.2201796647571055,"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."}}