{"id":"W2063014559","doi":"10.1038/srep06857","title":"Experimental Optimal Single Qubit Purification in an NMR Quantum Information Processor","year":2014,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; University of Waterloo; State Key Laboratory of Low-Dimensional Quantum Physics; Tsinghua University; National Natural Science Foundation of China","keywords":"Qubit; Quantum decoherence; Symmetrization; Protocol (science); Noise (video); Computer science; Scheme (mathematics); Topology (electrical circuits); Quantum computer; Quantum; Quantum mechanics; Physics; Mathematics; Electrical engineering; Engineering","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001426576,0.0001409647,0.0001403546,0.0003027642,0.0002848092,0.001199733,0.0004760676,0.00005749393,0.000006249778],"category_scores_gemma":[0.0000939864,0.0001282343,0.0000424945,0.0007011988,0.00009250753,0.001911213,0.0001431472,0.0001257018,0.00002545248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005281356,"about_ca_system_score_gemma":0.00008974995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001720732,"about_ca_topic_score_gemma":0.000004728138,"domain_scores_codex":[0.9979521,0.00007443933,0.0005251637,0.0006046671,0.0005161259,0.0003274826],"domain_scores_gemma":[0.998518,0.00002040187,0.0003092834,0.0009013242,0.0001324203,0.0001185365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003737973,0.00242701,0.004290541,0.0001699376,0.00001668629,0.0001943075,0.05066418,0.1764583,0.3114568,0.0273813,0.004031613,0.4228719],"study_design_scores_gemma":[0.0001306245,0.0001373705,0.0011533,0.00002830804,0.000001065473,0.000122521,0.00008923626,0.9335459,0.05326392,0.003345528,0.007972904,0.0002093621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.832612,0.00002847348,0.164262,0.0001828611,0.002236406,0.0002018472,2.856975e-7,0.0001866586,0.0002894881],"genre_scores_gemma":[0.9781661,8.619486e-8,0.0216058,0.00005392415,0.00006536653,0.00002094898,0.00002864381,0.000006122213,0.00005300222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7570875,"threshold_uncertainty_score":0.9998371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01139554120864955,"score_gpt":0.2407626758584165,"score_spread":0.229367134649767,"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."}}