{"id":"W2127226621","doi":"10.1109/4234.901815","title":"Using the Fourier transform to compute the weight distribution of a binary linear block code","year":2001,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Traverse; Trellis (graph); Code (set theory); Weight distribution; Algorithm; Computer science; Fourier transform; Discrete Fourier transform (general); Binary number; Block (permutation group theory); Polynomial code; Linear code; Fourier analysis; Cyclic code; Mathematics; Block code; Fractional Fourier transform; Decoding methods; Arithmetic; Mathematical analysis; Geometry; Programming language","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":[0.000254035,0.0001432611,0.0001493454,0.00006322972,0.0003938095,0.00001934179,0.001977673,0.00004868216,0.000003111704],"category_scores_gemma":[0.00001447067,0.0001062828,0.00008234368,0.0005860099,0.0002663688,0.0001275195,0.0001571403,0.0003660309,0.000006818863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001198665,"about_ca_system_score_gemma":0.00001292787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003866703,"about_ca_topic_score_gemma":0.00005664609,"domain_scores_codex":[0.9990769,0.0001328605,0.000351157,0.0000948095,0.0001556738,0.0001886258],"domain_scores_gemma":[0.9965282,0.0002924713,0.00007041525,0.002987165,0.00008146297,0.00004027472],"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":[0.00002917621,0.0001676244,0.0003240921,0.00004017009,0.0001894667,0.000001897092,0.002724535,0.7284006,0.2282467,0.003322643,0.01517572,0.02137733],"study_design_scores_gemma":[0.0002253948,0.00002337344,0.0006306395,0.0001132188,0.00005419393,0.00002976995,0.0001375391,0.6945318,0.023893,0.0002000361,0.2798716,0.0002894613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.175503,0.000624307,0.7906476,0.03167497,0.0001021871,0.0006441894,0.00006423775,0.0004020439,0.0003374444],"genre_scores_gemma":[0.948667,0.001150068,0.04919523,0.0007610962,0.00003771597,0.0001022918,0.0000432003,0.00003314968,0.00001019094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.773164,"threshold_uncertainty_score":0.4334085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0436192396430849,"score_gpt":0.3005955140509893,"score_spread":0.2569762744079044,"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."}}