{"id":"W2121821424","doi":"10.1109/lcomm.2002.807433","title":"Spreading code construction for CDMA","year":2003,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Hadamard transform; Computer science; Hadamard code; Diagonal; Code division multiple access; Code (set theory); Construct (python library); Trellis (graph); Algorithm; Block code; Set (abstract data type); Convolutional code; Hadamard matrix; Theoretical computer science; Decoding methods; Telecommunications; Mathematics; Computer network","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":[0.0002855563,0.0003838889,0.0002515966,0.0006173154,0.0004813248,0.0005107662,0.0003282981,0.000479472,0.001770427],"category_scores_gemma":[0.001225369,0.0002362126,0.0003720621,0.0005434955,0.0006145437,0.0004250078,0.000841772,0.001048323,0.0006952629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004608376,"about_ca_system_score_gemma":0.00065182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004460729,"about_ca_topic_score_gemma":0.0005054122,"domain_scores_codex":[0.9996336,0.00009500347,0.00001790525,0.00004598061,0.0001771757,0.00003033356],"domain_scores_gemma":[0.9996365,0.0001254796,0.00003008829,0.0001038683,0.00007884452,0.0000252459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008429294,0.00005303578,0.0003534803,0.0002391011,0.00003387732,0.0003263956,0.000343132,0.03749733,0.1117688,0.7080789,0.002484567,0.1387371],"study_design_scores_gemma":[0.0000854771,0.0003133476,0.000734934,0.0001896668,0.00006212907,0.001559769,0.00008593089,0.3139736,0.1693346,0.4271271,0.08638317,0.0001502787],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.043015,0.0007062587,0.9437462,0.0002824958,0.000176079,0.0001105496,0.0001247185,0.0003060281,0.0115327],"genre_scores_gemma":[0.361261,0.001036873,0.6287969,0.0002813898,0.0001066311,0.0002893074,0.0003976363,0.00009796349,0.007732176],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001770427,"threshold_uncertainty_score":0.005922675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06818355025977502,"score_gpt":0.3262687245303268,"score_spread":0.2580851742705518,"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."}}