{"id":"W2292278363","doi":"10.1007/s10776-016-0296-1","title":"Performance Analysis of the Double-Antenna SDC System Over N-Nakagami Fading Channels","year":2016,"lang":"en","type":"article","venue":"International Journal of Wireless Information Networks","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Natural Science Foundation of Shandong Province; National Natural Science Foundation of China","keywords":"Nakagami distribution; Fading; Computer science; Antenna (radio); Probability density function; Algorithm; Channel (broadcasting); Telecommunications; Cumulative distribution function; Statistics; Topology (electrical circuits); Mathematics; Combinatorics","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":[0.001437174,0.0009656087,0.001004994,0.0009494885,0.001052371,0.001795747,0.0005894863,0.001034902,0.004167736],"category_scores_gemma":[0.004321507,0.0002903778,0.0005183563,0.001199026,0.001084544,0.0008103792,0.001124542,0.0006036449,0.0005706599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002251093,"about_ca_system_score_gemma":0.001755524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01081702,"about_ca_topic_score_gemma":0.007663887,"domain_scores_codex":[0.9984206,0.000445493,0.00006851685,0.0001810691,0.0004003005,0.0004839638],"domain_scores_gemma":[0.9937003,0.003414462,0.0004821915,0.0003873223,0.001831071,0.0001845389],"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":[0.001417276,0.00009352906,0.009616589,0.0002954621,0.0002099122,0.0006641124,0.0003540452,0.9052726,0.03793042,0.0150724,0.001321594,0.02775216],"study_design_scores_gemma":[0.00001761623,0.0002250444,0.002009152,0.00001897765,0.00007128304,0.0002923664,0.00009776456,0.9910887,0.004595691,0.00119368,0.0003553581,0.00003436103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7327953,0.00239585,0.2356392,0.001019484,0.0001526694,0.0001028202,0.0004658476,0.0007549481,0.02667378],"genre_scores_gemma":[0.9962871,0.000203529,0.002439184,0.00003651288,0.00001995721,0.0000115068,0.00004927699,0.00001655526,0.0009363919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01081702,"threshold_uncertainty_score":0.0215081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01824743342134848,"score_gpt":0.2552014359197284,"score_spread":0.2369540024983799,"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."}}