{"id":"W4312725651","doi":"10.1109/lcomm.2022.3230202","title":"Dynamic Frozen-Function Design for Reed-Muller Codes With Automorphism-Based Decoding","year":2022,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Decoding methods; Permutation (music); Constraint (computer-aided design); Algorithm; Computer science; List decoding; Function (biology); Set (abstract data type); Mathematics; Block code; Concatenated error correction code; 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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0009195641,0.0001804943,0.0001789735,0.0003031683,0.001367517,0.0001290658,0.003099879,0.00003522963,0.000009190886],"category_scores_gemma":[0.00004889418,0.0001934901,0.00008304136,0.0006398758,0.0001211815,0.0002816257,0.0003997701,0.0003921318,0.000006804472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004006767,"about_ca_system_score_gemma":0.0001293111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005621231,"about_ca_topic_score_gemma":0.0000668699,"domain_scores_codex":[0.9983017,0.0004643695,0.000272809,0.0003857671,0.0002841294,0.00029126],"domain_scores_gemma":[0.9957143,0.001060358,0.0002315738,0.002830856,0.0001109648,0.00005193991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000592479,0.001271272,0.002072065,0.0001008323,0.0003952984,0.00002614885,0.004476388,0.433275,0.2940542,0.01951953,0.1908807,0.05333607],"study_design_scores_gemma":[0.0005101675,0.0003067704,0.0001781112,0.00003253862,0.00003300208,0.0000209814,0.00005868443,0.9867093,0.002396618,0.0006773914,0.008752208,0.0003242405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006290268,0.00008575765,0.9737225,0.01749786,0.000294282,0.0007454556,0.00000987042,0.001233,0.0001210593],"genre_scores_gemma":[0.5065683,0.000003548869,0.4892206,0.003225919,0.000006593878,0.0008959707,0.00002079331,0.00002361035,0.00003463781],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5534343,"threshold_uncertainty_score":0.9999326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04554918618501794,"score_gpt":0.2814449723953956,"score_spread":0.2358957862103777,"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."}}