{"id":"W2949438557","doi":"10.48550/arxiv.0801.3511","title":"Deterministic Design of Low-Density Parity-Check Codes for Binary Erasure Channels","year":2008,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Erasure; Parity (physics); Erasure code; Binary number; Low-density parity-check code; Binary erasure channel; Computer science; Mathematics; Arithmetic; Statistics; Algorithm; Physics; Decoding methods; Coding (social sciences); Programming language; Channel capacity; Atomic 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":[0.0007362345,0.0003209341,0.0003638866,0.0003795553,0.0004418868,0.0004808449,0.0005553066,0.0004696294,0.0005485088],"category_scores_gemma":[0.002462906,0.0002946081,0.0003365308,0.000337517,0.0006646307,0.0003801853,0.0006068106,0.0004974939,0.0001533628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006097337,"about_ca_system_score_gemma":0.0008831476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007242581,"about_ca_topic_score_gemma":0.001100438,"domain_scores_codex":[0.999328,0.0002256397,0.00003503127,0.00008688921,0.0002537523,0.00007075774],"domain_scores_gemma":[0.9986986,0.0005164121,0.0002685763,0.0002377571,0.0002340059,0.00004452022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000101426,0.0000471344,0.001534652,0.0001420413,0.00004766809,0.0000789684,0.0001112241,0.8340981,0.02234751,0.09730594,0.0007668606,0.04341844],"study_design_scores_gemma":[0.00001449675,0.00004781065,0.0001536058,0.000008582595,0.000008946148,0.00003842485,0.000007195305,0.9821101,0.00713989,0.009473117,0.0009847176,0.00001321096],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06599072,0.0001989995,0.9303984,0.0001744816,0.00004211806,0.00004602573,0.00006477967,0.0001831852,0.002901244],"genre_scores_gemma":[0.7555435,0.0001957355,0.2427261,0.00008416356,0.00002391624,0.000155393,0.00007132203,0.00003846082,0.001161469],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0007362345,"threshold_uncertainty_score":0.004423976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09757864263697298,"score_gpt":0.3057547996144752,"score_spread":0.2081761569775022,"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."}}