{"id":"W2511135871","doi":"10.1109/isit.2016.7541411","title":"Energy complexity of polar codes","year":2016,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Decoding methods; Polar; Coding (social sciences); Binary number; Upper and lower bounds; List decoding; Algorithm; Very-large-scale integration; Encoding (memory); Computer science; Probability of error; Block (permutation group theory); Block code; Discrete mathematics; Theoretical computer science; Mathematics; Arithmetic; Combinatorics; Concatenated error correction code; Statistics; Physics; Artificial intelligence","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":[0.0001541541,0.00006177324,0.0001040475,0.00006091734,0.00002569222,0.00001147186,0.0006658164,0.00002823906,0.00003835152],"category_scores_gemma":[0.00003415563,0.00003806803,0.00003815493,0.0001415397,0.00009663329,0.0001921089,0.0002330129,0.00002105992,0.00001019661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001867928,"about_ca_system_score_gemma":0.00002335782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004711189,"about_ca_topic_score_gemma":0.0001532774,"domain_scores_codex":[0.9993934,0.00004137477,0.0001331977,0.0001686204,0.0001358032,0.0001275972],"domain_scores_gemma":[0.9992581,0.000102105,0.00005960819,0.0004704203,0.0000745196,0.00003525227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000001287738,0.00002313976,0.002061398,0.000002194564,0.000003942622,0.000001068193,0.00004293895,5.750938e-8,0.04459194,0.9009681,0.002193547,0.05011044],"study_design_scores_gemma":[0.0001332364,0.0001158548,0.002713858,0.00003485116,0.000001371422,0.00001259737,0.000005619238,0.002195497,0.8099592,0.1786209,0.006041241,0.0001657372],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005756978,0.00001898191,0.9756784,0.000997028,0.00009449259,0.00002056129,0.000001385592,0.0005539318,0.01687826],"genre_scores_gemma":[0.8294608,0.000004982405,0.1697343,0.000136341,0.000010458,0.000001833767,1.045067e-7,0.000003191163,0.0006480003],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8237038,"threshold_uncertainty_score":0.1552369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04111977201120245,"score_gpt":0.2707083521516497,"score_spread":0.2295885801404472,"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."}}