{"id":"W2149891520","doi":"10.1109/pimrc.1995.476892","title":"Combined trellis/Reed-Muller coding for CDMA","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Convolutional code; Space–time trellis code; Biorthogonal system; Coding gain; Concatenated error correction code; Computer science; Algorithm; Decoding methods; Trellis (graph); Reed–Muller code; Constant-weight code; Code rate; Bit error rate; Theoretical computer science; Mathematics; Block code; 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":[0.000582047,0.0005100727,0.0003569414,0.0006353304,0.0003178816,0.0006408115,0.0005795719,0.0005402214,0.001312546],"category_scores_gemma":[0.001781325,0.0002184867,0.0003675614,0.0005411425,0.0004186484,0.000608304,0.0004029179,0.0004873456,0.0004998037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008165443,"about_ca_system_score_gemma":0.000726237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001314999,"about_ca_topic_score_gemma":0.002343587,"domain_scores_codex":[0.9991597,0.0002437157,0.0000327319,0.00006892612,0.0004293016,0.00006562128],"domain_scores_gemma":[0.9990633,0.0004468225,0.0001324378,0.0001325398,0.0002011676,0.00002374466],"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":[0.0007770293,0.0001246226,0.001102672,0.0005917097,0.0001353866,0.0005405653,0.0001472472,0.3955976,0.1969633,0.1444397,0.001769356,0.2578109],"study_design_scores_gemma":[0.00004121036,0.0003706348,0.0004294562,0.000048396,0.00007208797,0.0004913423,0.00001396559,0.9012021,0.06656358,0.02319129,0.007522672,0.00005322525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07567305,0.003524543,0.9125272,0.0002340212,0.0001089761,0.0000872356,0.0001066271,0.000663129,0.007075221],"genre_scores_gemma":[0.7143801,0.001696426,0.2764187,0.00009705981,0.0001846423,0.0001318456,0.0001338215,0.00006553106,0.006891904],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001314999,"threshold_uncertainty_score":0.005924404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03372337953982886,"score_gpt":0.2351844897939663,"score_spread":0.2014611102541374,"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."}}