{"id":"W4386897341","doi":"10.1103/prxquantum.4.030338","title":"Tailoring Three-Dimensional Topological Codes for Biased Noise","year":2023,"lang":"en","type":"article","venue":"PRX Quantum","topic":"Quantum and electron transport phenomena","field":"Physics and Astronomy","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; University of Waterloo; Perimeter Institute","funders":"Government of Canada; Institute for Quantum Information and Matter, California Institute of Technology; Ministry of Colleges and Universities; Engineering and Physical Sciences Research Council; Eidgenössische Technische Hochschule Zürich; National Centres of Competence in Research SwissMAP; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation; Institut Périmètre de physique théorique; National Science Foundation of Sri Lanka; Innovation, Science and Economic Development Canada; Simons Foundation","keywords":"Noise (video); Topology (electrical circuits); Noise reduction; Mathematics; Reduction (mathematics); Pauli exclusion principle; Computer science; Physics; Combinatorics; Quantum mechanics; Acoustics; Artificial intelligence; Geometry","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":[0.0001916253,0.0002370944,0.0001617215,0.0003539636,0.0002567442,0.0005100773,0.0003917445,0.0003615509,0.001347735],"category_scores_gemma":[0.001434061,0.0001128504,0.0001209248,0.0002934263,0.0005334668,0.0004761354,0.0005543192,0.0004794,0.0004275564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003201508,"about_ca_system_score_gemma":0.0003282311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002709577,"about_ca_topic_score_gemma":0.000850325,"domain_scores_codex":[0.999884,0.00001810323,0.00000975189,0.00001423171,0.00004927727,0.00002464951],"domain_scores_gemma":[0.9993389,0.0002132919,0.000119675,0.0001718312,0.0001141434,0.00004205345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002243203,0.0001543071,0.001712641,0.00009218062,0.00002176657,0.0001405742,0.000133856,0.04619693,0.7623293,0.1451229,0.0005597445,0.0433115],"study_design_scores_gemma":[0.00003734105,0.0002716571,0.001025018,0.00002955797,0.00001772309,0.0002316882,0.00005427482,0.3679828,0.5844253,0.04185073,0.004001387,0.0000724635],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8678975,0.0001317438,0.1231649,0.0002393655,0.00007066932,0.000034542,0.0001058235,0.0004836724,0.007871766],"genre_scores_gemma":[0.9805806,0.00007586137,0.01789171,0.00004997536,0.00001173059,0.00002638965,0.00005762919,0.00005782043,0.00124834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001347735,"threshold_uncertainty_score":0.004508555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03489405855930276,"score_gpt":0.2715332242908184,"score_spread":0.2366391657315156,"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."}}