{"id":"W2963924687","doi":"10.1109/isit.2018.8437465","title":"From Cages to Trapping Sets: A New Technique to Derive Tight Upper Bounds on the Minimum Size of Trapping Sets and Minimum Distance of LDPC Codes","year":2018,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Low-density parity-check code; Mathematics; Trapping; Girth (graph theory); Combinatorics; Upper and lower bounds; Minimum weight; Discrete mathematics; Degree (music); Minimum distance; Cage; Graph theory; Decoding methods; Algorithm; Physics","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":[0.001293639,0.002068637,0.001295142,0.003266901,0.001053769,0.001443519,0.002110698,0.001245945,0.003415071],"category_scores_gemma":[0.0106897,0.000924671,0.001832406,0.002133934,0.002554155,0.004281893,0.004099349,0.004773194,0.001035149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001245683,"about_ca_system_score_gemma":0.0007596778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009776875,"about_ca_topic_score_gemma":0.00139753,"domain_scores_codex":[0.9987566,0.0002895774,0.00008938377,0.0003033996,0.0004064712,0.0001544297],"domain_scores_gemma":[0.9911006,0.006015572,0.0006197704,0.001327306,0.000635698,0.0003010001],"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":[0.0001792714,0.0001626447,0.001878497,0.0006696822,0.0001616924,0.0005445376,0.0006242553,0.2192082,0.0391649,0.6640911,0.006908081,0.06640729],"study_design_scores_gemma":[0.00002632253,0.000209785,0.001026037,0.0001445085,0.0001126103,0.0006431486,0.0001325336,0.5348127,0.0199908,0.4291134,0.01367404,0.0001139904],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02065376,0.001050795,0.9685928,0.000248858,0.0001080922,0.00007255897,0.0002701879,0.0003673974,0.008635595],"genre_scores_gemma":[0.5003625,0.004760684,0.4818577,0.0009863297,0.0005386847,0.000853377,0.001220069,0.0009408953,0.008479652],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003415071,"threshold_uncertainty_score":0.0114246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0201859941141127,"score_gpt":0.2811892868468568,"score_spread":0.2610032927327441,"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."}}