{"id":"W2083041493","doi":"10.1103/physrevlett.94.180501","title":"Unified and Generalized Approach to Quantum Error Correction","year":2005,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":295,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Perimeter Institute; University of Waterloo","funders":"","keywords":"Quantum error correction; Error detection and correction; Decoherence-free subspaces; Quantum decoherence; Quantum; Computer science; Linear subspace; Operator (biology); Algorithm; Quantum capacity; Quantum algorithm; Quantum mechanics; Quantum computer; Mathematics; Physics; Quantum network; Pure mathematics","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":[0.0001503888,0.0001195477,0.0002070732,0.00006339996,0.00006891804,0.00007248569,0.0002808522,0.000006835409,0.000003660799],"category_scores_gemma":[0.00001807159,0.0000968149,0.0000927744,0.0004721067,0.00002639662,0.0004256551,0.00007029476,0.00009400259,0.0001361365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001606924,"about_ca_system_score_gemma":0.000007637854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006935082,"about_ca_topic_score_gemma":5.447439e-7,"domain_scores_codex":[0.999152,0.00006315876,0.0001884165,0.0002168298,0.0002006662,0.0001789141],"domain_scores_gemma":[0.9994692,0.00002715507,0.00006317978,0.0002845392,0.00002619653,0.0001297329],"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":[0.00001408834,0.0004697281,0.00007128575,0.0008657002,0.00005077252,0.000001348558,0.001609412,0.001645605,0.006232262,0.4654447,0.2905802,0.233015],"study_design_scores_gemma":[0.0003537782,0.00005376481,0.001217598,0.0002342623,0.00002412836,0.00001545861,0.00001351775,0.7495022,0.0003021688,0.0004417817,0.247448,0.0003932966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1933562,0.001859521,0.7640027,0.03697733,0.0003602991,0.0007110508,0.000001277585,0.0003143832,0.002417229],"genre_scores_gemma":[0.7986091,0.001317439,0.02409689,0.1755677,0.0002528527,0.0001106819,0.000008209444,0.00001185668,0.00002518153],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7478566,"threshold_uncertainty_score":0.3947997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02390449772794459,"score_gpt":0.2812254180696845,"score_spread":0.2573209203417399,"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."}}