{"id":"W2127194094","doi":"10.1109/innovations.2008.4781688","title":"A convolutionally coded CDMA system with transmit diversity over Nakagami fading channels","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Fading; Nakagami distribution; Pairwise error probability; Phase-shift keying; Computer science; Transmit diversity; Convolutional code; Algorithm; Bit error rate; Diversity scheme; Electronic engineering; Channel state information; Code division multiple access; Telecommunications; Topology (electrical circuits); Channel (broadcasting); Mathematics; Decoding methods; Wireless; Engineering","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":[0.000696585,0.0009232471,0.0006396759,0.0003295785,0.0005621304,0.0007483588,0.0005994498,0.000950571,0.0006788364],"category_scores_gemma":[0.00256137,0.0002220767,0.000239537,0.0006897164,0.000875436,0.0005863386,0.0005423302,0.0003932607,0.0001267283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001001413,"about_ca_system_score_gemma":0.001294316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01109686,"about_ca_topic_score_gemma":0.0106646,"domain_scores_codex":[0.9993475,0.000156084,0.00003036957,0.00008023306,0.000212287,0.0001735065],"domain_scores_gemma":[0.9982052,0.0008573466,0.0002346864,0.0001670965,0.0004470736,0.00008867743],"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":[0.0006705365,0.0001077916,0.006367129,0.0001299322,0.00009274597,0.0008277395,0.0001767311,0.9194108,0.04467104,0.008715695,0.0002722479,0.01855767],"study_design_scores_gemma":[0.00002915896,0.0002021826,0.001027206,0.000006508285,0.00004047216,0.0001670051,0.00001918959,0.9885766,0.008775312,0.0009355521,0.0001993257,0.00002159437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.859384,0.0002642523,0.1355465,0.0001756934,0.00003624424,0.00006138835,0.0001139672,0.0002258712,0.004192127],"genre_scores_gemma":[0.9924971,0.00007468696,0.006649689,0.0000168165,0.00000861339,0.0000133882,0.00002876148,0.000002602663,0.0007083953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01109686,"threshold_uncertainty_score":0.02206457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686721870977543,"score_gpt":0.1999515434690742,"score_spread":0.1830843247592988,"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."}}