{"id":"W4361269916","doi":"10.1002/jcd.21882","title":"Ordered covering arrays and upper bounds on covering codes","year":2023,"lang":"en","type":"article","venue":"Journal of Combinatorial Designs","topic":"Coding theory and cryptography","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Ottawa","funders":"Ciência sem Fronteiras; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ministério da Ciência, Tecnologia e Inovação; Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Mathematics; Upper and lower bounds; Combinatorics; Concatenation (mathematics); Cartesian product; Hamming code; Hamming distance; Discrete mathematics; Connection (principal bundle); Product (mathematics); Block code; Algorithm; Decoding methods; Geometry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001076442,0.000142306,0.0002674961,0.0003342769,0.0002155961,0.000328437,0.0005221395,0.00006621444,0.00000647384],"category_scores_gemma":[0.000125507,0.0001275047,0.0001285741,0.0006402688,0.00005233991,0.0004834944,0.0001242325,0.0002508512,0.0000130282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003625222,"about_ca_system_score_gemma":0.0000782279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002736706,"about_ca_topic_score_gemma":2.810529e-7,"domain_scores_codex":[0.9987281,0.0001341663,0.0003167533,0.0001687042,0.0003981766,0.0002540769],"domain_scores_gemma":[0.9988612,0.0004471555,0.0002116121,0.0002265223,0.0001166803,0.0001368445],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001921036,0.00008286064,0.0009977915,0.00002052493,0.00007886987,0.0001050512,0.0006376035,0.0003961044,0.01110387,0.980904,0.001438475,0.004042744],"study_design_scores_gemma":[0.004126923,0.003002503,0.005932264,0.0003653309,0.00005040986,0.0001927962,0.00019255,0.003866376,0.01856122,0.942591,0.02051823,0.0006004194],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.808066,0.0001599566,0.1794347,0.0005846691,0.009141016,0.0001283495,0.000002149854,0.0001830113,0.002300197],"genre_scores_gemma":[0.998096,0.00008431393,0.001364584,0.00009019076,0.0003169828,0.000001680923,2.695552e-7,0.00001194583,0.00003395728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1900301,"threshold_uncertainty_score":0.519949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02489971877531201,"score_gpt":0.2561583306077486,"score_spread":0.2312586118324366,"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."}}