{"id":"W2118552966","doi":"10.1109/tit.2010.2053873","title":"Distance Bounds for Periodically Time-Varying and Tail-Biting LDPC Convolutional Codes","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Convolutional code; Serial concatenated convolutional codes; Low-density parity-check code; Turbo code; Mathematics; Upper and lower bounds; Concatenated error correction code; Bounding overwatch; Discrete mathematics; Combinatorics; Algorithm; Block code; Computer science; Decoding methods","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":[0.001542194,0.001032909,0.0007229852,0.00149758,0.0007748754,0.001559818,0.001788348,0.001346919,0.002880343],"category_scores_gemma":[0.01336016,0.0004430945,0.0005480285,0.00125191,0.001671509,0.00292578,0.002521572,0.002836677,0.0006329245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002165725,"about_ca_system_score_gemma":0.001147058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001086881,"about_ca_topic_score_gemma":0.001160009,"domain_scores_codex":[0.9985851,0.0002128548,0.00009018383,0.0002777143,0.000619567,0.0002145281],"domain_scores_gemma":[0.9877537,0.008221245,0.0009834819,0.001271684,0.00134897,0.0004209705],"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":[0.0007785171,0.0001056379,0.002186376,0.0006701592,0.0001007074,0.0004516783,0.000667833,0.2939945,0.05012478,0.5346419,0.003928841,0.1123491],"study_design_scores_gemma":[0.00003395959,0.0001989635,0.001383699,0.0001227253,0.00005135511,0.0004995072,0.0001193801,0.6434302,0.03370454,0.3141179,0.00622534,0.0001124175],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1308875,0.006170777,0.836943,0.001179438,0.0002070243,0.00006122096,0.0005437531,0.000530195,0.02347703],"genre_scores_gemma":[0.8704684,0.002878057,0.1157922,0.0003931218,0.0001679046,0.0001737716,0.0007008421,0.0002382769,0.009187534],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002880343,"threshold_uncertainty_score":0.01571345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006618558313170579,"score_gpt":0.232299132713384,"score_spread":0.2256805744002134,"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."}}