{"id":"W2149792368","doi":"10.1109/isit.2010.5513275","title":"On the error exponent to redundancy ratio of interactive encoding and decoding","year":2010,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Decoding methods; Exponent; Redundancy (engineering); Encoding (memory); Computer science; Coding (social sciences); Algorithm; Probability of error; Ergodic theory; Low-density parity-check code; Source code; Theoretical computer science; Error detection and correction; Discrete mathematics; Mathematics; Statistics; Artificial intelligence; Pure mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001408583,0.00006150347,0.00007358858,0.00006172573,0.00003911273,0.00002166307,0.0001647554,0.00002856234,0.00009659834],"category_scores_gemma":[0.0001101403,0.00004628865,0.00001562711,0.00006580988,0.00002109578,0.00008003453,0.00006704043,0.0001952252,0.000006292502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001477163,"about_ca_system_score_gemma":0.000003393942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001601096,"about_ca_topic_score_gemma":0.00007224672,"domain_scores_codex":[0.999665,0.00001620544,0.0001267663,0.00006313637,0.0000621806,0.00006666825],"domain_scores_gemma":[0.9993451,0.0002758494,0.00002042665,0.0003025662,0.00002840256,0.000027676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008393095,0.00002146802,0.0001417769,0.00001558247,0.00001796318,2.951604e-7,0.005342018,0.0001325416,0.8002287,0.1850591,0.001756645,0.00727556],"study_design_scores_gemma":[0.00006217744,0.00003126424,0.0008782844,0.00007166385,0.000002968641,0.000002167253,0.0005761672,0.01784134,0.9769405,0.001856284,0.001623187,0.0001140041],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9681799,0.00001285983,0.01194965,0.0008051619,0.00007985011,0.0001712286,0.000001271962,0.0001797407,0.01862029],"genre_scores_gemma":[0.9918446,0.00001607753,0.007976364,0.00008107318,0.000009893557,0.00003302235,5.376178e-7,0.00001041717,0.00002804659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1832028,"threshold_uncertainty_score":0.1887596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01833751768126094,"score_gpt":0.2715608432621843,"score_spread":0.2532233255809233,"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."}}