{"id":"W3089835555","doi":"10.1109/tcomm.2020.3028302","title":"Construction of Irregular Protograph-Based QC-LDPC Codes With Low Error Floor","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Low-density parity-check code; Tanner graph; Algorithm; Error floor; Computer science; Block code; Set (abstract data type); Block (permutation group theory); Graph; Decoding methods; Mathematics; Theoretical computer science; Combinatorics","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":[0.0001790746,0.0002046504,0.0002556601,0.0002536922,0.0003976542,0.00006077143,0.001926474,0.00009180703,0.00001963915],"category_scores_gemma":[0.00001445404,0.0001985017,0.0001407721,0.001395143,0.0004551478,0.0003197818,0.00001304103,0.0004572202,0.00001657269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004441545,"about_ca_system_score_gemma":0.0002017608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001000951,"about_ca_topic_score_gemma":0.0001759819,"domain_scores_codex":[0.9985218,0.0002335678,0.0003778974,0.0003549865,0.000309377,0.0002023577],"domain_scores_gemma":[0.9968181,0.0002077146,0.0002183203,0.002331928,0.0002974701,0.0001265005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001464028,0.0111886,0.002226899,0.001584824,0.001574824,0.00003135495,0.02215482,0.1234062,0.2072763,0.06288969,0.001920966,0.5642815],"study_design_scores_gemma":[0.00123362,0.001282242,0.0003079477,0.0004229273,0.0001175111,0.00003853384,0.0003784503,0.4466178,0.5463352,0.000951656,0.00165035,0.0006637942],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004841144,0.00003446154,0.9864389,0.006174995,0.00009479072,0.0009048033,0.00003048828,0.000983709,0.0004967234],"genre_scores_gemma":[0.6597033,0.00001784831,0.3396915,0.0002257877,0.000005685287,0.0003257022,0.000003730271,0.00001674472,0.000009687897],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6548621,"threshold_uncertainty_score":0.8094667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03212018938070391,"score_gpt":0.2695646230738625,"score_spread":0.2374444336931586,"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."}}