{"id":"W2951012470","doi":"10.48550/arxiv.1304.6100","title":"Fault-Tolerant Renormalization Group Decoder for Abelian Topological Codes","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Cellular Automata and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Intelligence Advanced Research Projects Activity; Compute Canada","keywords":"Abelian group; Generalization; Decoding methods; Fault tolerance; Computer science; Logarithm; Code (set theory); Mathematics; Algorithm; Topology (electrical circuits); Discrete mathematics; Combinatorics; Set (abstract data type)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003881288,0.0002393245,0.0004182291,0.0003649611,0.0004551091,0.0005975426,0.0007625968,0.0008798631,0.001213438],"category_scores_gemma":[0.002316665,0.0001327401,0.0003012745,0.0002991867,0.0008222437,0.000733704,0.000898511,0.0006101804,0.0003745067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007579358,"about_ca_system_score_gemma":0.000821892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007624755,"about_ca_topic_score_gemma":0.0008746373,"domain_scores_codex":[0.9996737,0.00008200215,0.00002385466,0.00004623243,0.0001256328,0.00004858559],"domain_scores_gemma":[0.9990976,0.0003235958,0.00009449896,0.0002917543,0.0001459375,0.00004673378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004138062,0.0001267719,0.002013504,0.0001442601,0.00005618436,0.0004346293,0.0003971083,0.262817,0.1181783,0.513179,0.002465728,0.09977369],"study_design_scores_gemma":[0.00003822452,0.00006893589,0.0002549431,0.000008535464,0.000006477234,0.0001202256,0.00001981028,0.8821108,0.038886,0.07639051,0.002062296,0.00003317392],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3310618,0.000154562,0.6591325,0.0005590568,0.000125294,0.00007982206,0.00012078,0.00118274,0.007583384],"genre_scores_gemma":[0.8055831,0.00005834525,0.1918342,0.0001396327,0.00002033843,0.00007585845,0.00007802372,0.00008241302,0.002127967],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001213438,"threshold_uncertainty_score":0.005499184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06997492243038628,"score_gpt":0.202539798894542,"score_spread":0.1325648764641557,"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."}}