{"id":"W1928225244","doi":"10.1109/vetec.1999.778051","title":"Performance of concatenated Walsh/PN spreading sequences for CDMA systems","year":2003,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Rake receiver; Rician fading; Bit error rate; Rake; Code division multiple access; Algorithm; Computer science; Multipath propagation; Additive white Gaussian noise; Electronic engineering; Fading; Telecommunications; White noise; Channel (broadcasting); Engineering; Decoding methods","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008820063,0.00008676822,0.0001732185,0.00009585098,0.0001221726,0.00009759447,0.00129049,0.00005267001,0.00001251309],"category_scores_gemma":[0.00008198268,0.00007023263,0.00003820063,0.0004737557,0.0000769968,0.0004100659,0.0001293131,0.00008922224,0.00001602515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000498501,"about_ca_system_score_gemma":0.0001032107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000644597,"about_ca_topic_score_gemma":0.000004262228,"domain_scores_codex":[0.9988136,0.000148444,0.0002943746,0.0002061961,0.0002537698,0.0002835627],"domain_scores_gemma":[0.9983968,0.0004113625,0.0001101245,0.0007319606,0.0002825446,0.00006719353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001810467,0.0001071659,0.01113763,0.0003377992,0.00007510428,0.000001716147,0.0007545559,0.02577042,0.01392689,0.9311626,0.002708053,0.01399996],"study_design_scores_gemma":[0.0002448244,0.00009198199,0.0002749213,0.00005810472,0.000001741283,0.000008829353,0.00007084098,0.9714148,0.0245798,0.0001885106,0.002952126,0.0001134824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5089719,0.000989445,0.4355498,0.0004846405,0.0005507772,0.001148846,0.000003213809,0.0002981088,0.0520033],"genre_scores_gemma":[0.9805842,0.0001110505,0.01774858,0.00002060124,0.00001185521,0.00007035231,0.000001803131,0.000006721493,0.00144486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9456444,"threshold_uncertainty_score":0.2864003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0504063838357585,"score_gpt":0.297171593941225,"score_spread":0.2467652101054665,"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."}}