{"id":"W4403310488","doi":"10.22331/q-2024-10-10-1498","title":"Decoding algorithms for surface codes","year":2024,"lang":"en","type":"article","venue":"Quantum","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Photon Etc (Canada)","funders":"Ministerio de Ciencia e Innovación; Ministerio de Economía y Competitividad; European Commission","keywords":"Decoding methods; Computer science; Algorithm; List decoding; Sequential decoding; Concatenated error correction code; Block code","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":[0.0001812319,0.0000985766,0.0001066627,0.00006438539,0.00007877211,0.0001676622,0.0007653626,0.00005054396,0.000003503241],"category_scores_gemma":[0.00008968094,0.00008693514,0.00004435235,0.0003009326,0.00004588404,0.0006471545,0.0002570716,0.00009675961,0.00008650705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004413624,"about_ca_system_score_gemma":0.00003345011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000515081,"about_ca_topic_score_gemma":0.000002150938,"domain_scores_codex":[0.9991482,0.000008340999,0.0001204793,0.0003641684,0.0001092436,0.0002495154],"domain_scores_gemma":[0.9991807,0.0002714093,0.00002150716,0.0004697917,0.000027918,0.00002868941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001034873,0.000007182944,0.00000661737,0.00003520625,0.000009685327,0.00002955129,0.00008596766,0.00009814827,0.002006595,0.8283913,0.005725383,0.1636034],"study_design_scores_gemma":[0.0000593492,0.00005606787,0.00001025893,0.00003416278,0.000003070421,0.00001464022,0.00004013819,0.778694,0.01018535,0.1540937,0.05666487,0.000144357],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003068078,0.002464265,0.9900669,0.001155885,0.0008915483,0.0001346915,0.00003348341,0.002061286,0.0001238875],"genre_scores_gemma":[0.2226496,0.00009547635,0.7768412,0.00006951445,0.00004934016,0.00002180882,0.000007413536,0.00001495222,0.0002506866],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7785959,"threshold_uncertainty_score":0.3545112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04933901699950013,"score_gpt":0.3259667094915187,"score_spread":0.2766276924920186,"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."}}