{"id":"W2758267643","doi":"10.1109/twc.2017.2755017","title":"Design and Analysis of Hierarchical Physical Layer Network Coding","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Relay; Computer science; Linear network coding; Computer network; Relay channel; Node (physics); Phase-shift keying; Channel (broadcasting); Wireless; Physical layer; Bit error rate; Telecommunications; Network packet; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001147133,0.0006663419,0.0003954419,0.0006638669,0.0004051676,0.0007709523,0.0009292707,0.000436035,0.001544645],"category_scores_gemma":[0.003086916,0.000381216,0.0003549466,0.000760538,0.0008270504,0.00102453,0.0008761241,0.0007197768,0.000335538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001895312,"about_ca_system_score_gemma":0.002157827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004987478,"about_ca_topic_score_gemma":0.005409862,"domain_scores_codex":[0.998906,0.0002849064,0.00004516884,0.0001236124,0.0005097537,0.0001305094],"domain_scores_gemma":[0.9985423,0.0006651354,0.0001577674,0.0001576372,0.0004393812,0.0000378076],"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":[0.00005505226,0.00002729785,0.0005490396,0.000108286,0.00002380921,0.0001184531,0.00009609226,0.7966633,0.01058189,0.131725,0.00130589,0.05874573],"study_design_scores_gemma":[0.000005754585,0.00003180575,0.00008242358,0.00001144767,0.000007049333,0.00003535099,0.000009086516,0.9861221,0.001494964,0.01096032,0.00123118,0.000008590741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005877044,0.0002683535,0.9884527,0.0001005189,0.0000231609,0.00005555937,0.00005722328,0.0001008365,0.005064468],"genre_scores_gemma":[0.6318829,0.001224369,0.3622027,0.000147232,0.00006681061,0.0003326459,0.0002463064,0.00005425556,0.003842666],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004987478,"threshold_uncertainty_score":0.01375151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08415139727514076,"score_gpt":0.328688036756599,"score_spread":0.2445366394814583,"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."}}