{"id":"W2043859521","doi":"10.1002/ett.1133","title":"The input–output weight enumeration of binary Hamming codes","year":2006,"lang":"en","type":"article","venue":"European Transactions on Telecommunications","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"České Vysoké Učení Technické v Praze","keywords":"Hamming(7,4); Hamming graph; Hamming bound; Hamming code; Antipodal point; Hamming weight; Linear code; Algorithm; Hamming distance; Hamming space; Mathematics; Block code; Enumeration; Coding gain; Binary number; Discrete mathematics; Computer science; Decoding methods; Arithmetic","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":[0.0005703062,0.000360158,0.0002818475,0.0007615812,0.0003970573,0.001041349,0.000538376,0.0004395401,0.003086936],"category_scores_gemma":[0.003841159,0.0001907082,0.0002557032,0.0006027375,0.0005895582,0.001206003,0.0009112552,0.0005905944,0.0008603762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005207791,"about_ca_system_score_gemma":0.000669517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006460435,"about_ca_topic_score_gemma":0.0007417992,"domain_scores_codex":[0.9993039,0.0001744296,0.00004581302,0.00006874424,0.0002991938,0.0001077614],"domain_scores_gemma":[0.9989941,0.0004917049,0.00009125684,0.000147472,0.0002373229,0.00003821948],"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":[0.0003238533,0.00007482908,0.001384356,0.0001745081,0.00002423842,0.0001483905,0.0001873512,0.09811796,0.04906232,0.6768929,0.001970474,0.1716388],"study_design_scores_gemma":[0.00004100514,0.00009993718,0.0006305093,0.00007345738,0.00001829755,0.0002003346,0.00003528411,0.5795285,0.06830877,0.3451703,0.005851382,0.00004234202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2008884,0.0003083389,0.7813886,0.0001996396,0.00008349412,0.0000831997,0.0002604092,0.0004434219,0.01634446],"genre_scores_gemma":[0.7670797,0.0002480957,0.2246587,0.00009392147,0.00003596814,0.0001283599,0.0004024562,0.0001482173,0.00720464],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003086936,"threshold_uncertainty_score":0.0103268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009488280066091774,"score_gpt":0.2174941328018628,"score_spread":0.208005852735771,"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."}}