{"id":"W2977160802","doi":"10.1109/lcomm.2019.2942919","title":"Coverage Analysis of Cooperative NOMA in Millimeter Wave Networks","year":2019,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Noma; Relay; Decoding methods; Computer science; Computer network; Transmission (telecommunications); Selection (genetic algorithm); Set (abstract data type); Telecommunications; Algorithm; Telecommunications link; Power (physics); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001160733,0.0001362689,0.0003353308,0.0005497745,0.0000412223,0.00001428839,0.001073858,0.00008396324,0.00003291418],"category_scores_gemma":[0.00001930703,0.0001500044,0.00009488656,0.001625995,0.0001601972,0.0001696565,0.0001852184,0.0003712203,0.0000182303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001123194,"about_ca_system_score_gemma":0.000005823442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002067619,"about_ca_topic_score_gemma":0.000142297,"domain_scores_codex":[0.9991422,0.00009204984,0.0003795292,0.0001299329,0.00008470742,0.0001716185],"domain_scores_gemma":[0.9963936,0.0004180702,0.00008129423,0.003040124,0.00004759564,0.00001934844],"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":[0.000002880461,0.00002877852,0.006270552,0.000006695581,0.0002948402,4.179128e-7,0.0002224008,0.9679793,0.02183582,0.0005462235,0.0001514278,0.002660633],"study_design_scores_gemma":[0.0003279643,0.00001441621,0.01859657,0.00003869469,0.00007759548,6.639672e-7,0.0001592255,0.9738163,0.005295849,0.00003519218,0.001373017,0.0002644753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8277077,0.001130899,0.1681874,0.0008409959,0.00008530488,0.0002961271,0.00002312194,0.0002682688,0.001460165],"genre_scores_gemma":[0.989809,0.001716702,0.008058576,0.0002387998,0.000002929173,0.00006277039,0.0000730649,0.00002236742,0.00001573507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1621014,"threshold_uncertainty_score":0.6117004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01869713631260678,"score_gpt":0.2410975411436078,"score_spread":0.222400404831001,"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."}}