{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006272203,0.0006051868,0.0004858838,0.0003618275,0.000274196,0.0006061988,0.000482489,0.000613597,0.0008771064],"category_scores_gemma":[0.001654286,0.0002240048,0.0002960931,0.0004461474,0.000503108,0.0007738564,0.0005251995,0.000297375,0.0002427887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004328176,"about_ca_system_score_gemma":0.0002323574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005991585,"about_ca_topic_score_gemma":0.0005396308,"domain_scores_codex":[0.9995097,0.0002804196,0.00001069551,0.00005066721,0.00009976096,0.00004877459],"domain_scores_gemma":[0.9991788,0.0006161961,0.00008723739,0.00004554449,0.0000541412,0.00001797446],"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":[0.0001314898,0.00004532572,0.001246921,0.0001171806,0.00007115147,0.0004752807,0.0001344554,0.8973092,0.01483176,0.05946127,0.0009499809,0.02522602],"study_design_scores_gemma":[0.00001514655,0.00008417758,0.0003022383,0.000007690144,0.00001664482,0.0001875393,0.00003475284,0.9865594,0.001821183,0.009629532,0.001330377,0.0000113383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1009169,0.002391597,0.890219,0.0004584515,0.00008292199,0.00004060069,0.00005307118,0.0001319312,0.005705559],"genre_scores_gemma":[0.9689205,0.001429502,0.02704732,0.00006179613,0.0000588368,0.0000573693,0.00002837296,0.00001302877,0.00238319],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008771064,"threshold_uncertainty_score":0.003317118,"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."}}