{"id":"W1574567957","doi":"10.1049/el.2014.4432","title":"237 Gbit/s unrolled hardware polar decoder","year":2015,"lang":"en","type":"article","venue":"Electronics Letters","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; McGill University","funders":"","keywords":"Decoding methods; Polar code; Polar; Soft-decision decoder; Throughput; Code (set theory)","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":[0.0006516395,0.0002349188,0.0002302929,0.0001826998,0.000116681,0.000181948,0.001439972,0.00008944333,0.000007020049],"category_scores_gemma":[0.0001448413,0.0002378077,0.0001068712,0.000520575,0.00003467462,0.0004856579,0.0002760216,0.0004801633,0.0001462818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004540617,"about_ca_system_score_gemma":0.0002842559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005613923,"about_ca_topic_score_gemma":0.00007149739,"domain_scores_codex":[0.9978672,0.0001342759,0.0002489272,0.0005244351,0.0004674033,0.0007577253],"domain_scores_gemma":[0.9985954,0.00007520687,0.0001164332,0.0009114257,0.0001135583,0.0001879672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001061947,0.0003037831,0.007591917,0.00003938239,0.0002586671,0.0003166813,0.006642637,0.001103344,0.08593038,0.06380614,0.7879804,0.04592042],"study_design_scores_gemma":[0.004447415,0.001579118,0.001127444,0.0001348261,0.00008567358,0.0006094181,0.0001330054,0.09132687,0.2111249,0.0395101,0.6463268,0.003594388],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07701106,0.001060107,0.8978761,0.01847021,0.0007664365,0.0003127464,0.000001323156,0.002100017,0.002401979],"genre_scores_gemma":[0.8822491,0.000024589,0.1026205,0.01432067,0.0002070004,0.00005015691,0.000007439266,0.00006116053,0.0004593149],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8052381,"threshold_uncertainty_score":0.9697515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01733987392950084,"score_gpt":0.248597022633858,"score_spread":0.2312571487043572,"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."}}