{"id":"W2122599120","doi":"10.1109/glocom.2008.ecp.206","title":"Characterization of Relay Channels Using the Bhattacharyya Parameter","year":2008,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Demodulation; Bhattacharyya distance; Relay; Decoding methods; Computer science; Code word; Algorithm; Signal-to-noise ratio (imaging); Estimation theory; Frame (networking); Noise (video); Telecommunications; Physics; Artificial intelligence","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":[0.002621782,0.001259371,0.001203538,0.001684612,0.001076953,0.002681737,0.001398775,0.001461748,0.002769806],"category_scores_gemma":[0.01636684,0.0004680204,0.000528695,0.00121007,0.003272698,0.005453093,0.002298464,0.002949082,0.0008275369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001714657,"about_ca_system_score_gemma":0.0009069186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001221593,"about_ca_topic_score_gemma":0.0004581205,"domain_scores_codex":[0.9983802,0.0005940354,0.00006927708,0.0002632208,0.0004722048,0.0002209791],"domain_scores_gemma":[0.9893849,0.007634069,0.0009528691,0.0009253995,0.0008433704,0.0002592886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000183754,0.00004187421,0.0007879112,0.0001546596,0.00003535219,0.0001527348,0.0003393625,0.3971844,0.01162834,0.5683678,0.001022203,0.02010168],"study_design_scores_gemma":[0.00001677602,0.00006274552,0.0004641598,0.00006684981,0.00001534152,0.0002885867,0.0000916537,0.7865829,0.006541537,0.2035023,0.002276581,0.00009045858],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04777964,0.001282225,0.9370753,0.0003170699,0.00003715219,0.00005120478,0.0001356165,0.000197057,0.01312472],"genre_scores_gemma":[0.9386652,0.001928511,0.05573799,0.000140096,0.0001035622,0.000231004,0.0001735615,0.0001688536,0.002851114],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002769806,"threshold_uncertainty_score":0.01386547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1003106467258358,"score_gpt":0.2959010774709747,"score_spread":0.1955904307451389,"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."}}