{"id":"W2951987143","doi":"10.26421/qic6.4-5-6","title":"Operator quantum error correction","year":2006,"lang":"en","type":"article","venue":"Quantum Information and Computation","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Agricultural Research Development Agency","keywords":"Quantum error correction; Decoherence-free subspaces; Linear subspace; Quantum; Operator (biology); Quantum decoherence; Error detection and correction; Formalism (music); Computer science; Algorithm; Quantum operation; Mathematics; Quantum algorithm; Quantum mechanics; Open quantum system; Pure mathematics; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002995032,0.0001833409,0.0001537156,0.0004345614,0.0003528532,0.000702447,0.0002245726,0.00009107994,0.000016651],"category_scores_gemma":[0.00002227013,0.0001753975,0.0000650377,0.0006720381,0.00004986791,0.005406835,0.00006623959,0.0001324409,0.0002851034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003689748,"about_ca_system_score_gemma":0.0000624196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001028141,"about_ca_topic_score_gemma":0.000009779541,"domain_scores_codex":[0.9985463,0.00005483058,0.0006394995,0.000164584,0.000356912,0.0002378592],"domain_scores_gemma":[0.9991267,0.00005078496,0.0002832936,0.0001940294,0.0002548464,0.00009034146],"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":[0.00001633388,0.00004844073,0.0005033523,0.00004403999,0.000009281415,7.618311e-7,0.001029237,0.005212147,0.00006622445,0.8898453,0.01790052,0.08532438],"study_design_scores_gemma":[0.0005570197,0.00009640092,0.01247129,0.00001454727,0.000004435597,0.00003846859,0.0003824201,0.9531136,0.000219566,0.01383886,0.0190202,0.0002432488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1224187,0.00004990469,0.8707612,0.0005839836,0.001205337,0.0002222434,0.000003483829,0.0004937488,0.004261417],"genre_scores_gemma":[0.9947313,0.00001936932,0.003991036,0.001012832,0.00005595792,0.00002514706,0.0001244247,0.000005606636,0.00003433716],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9479014,"threshold_uncertainty_score":0.7152504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009021169394826136,"score_gpt":0.2346620443819905,"score_spread":0.2256408749871643,"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."}}