{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009484035,0.0003432249,0.0004944726,0.0001991577,0.0006752734,0.0004218159,0.0008346412,0.0006430792,0.00222125],"category_scores_gemma":[0.001342322,0.0003422596,0.00014337,0.0003584095,0.001185017,0.000936017,0.0009663371,0.0008739471,0.0003949883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004117338,"about_ca_system_score_gemma":0.0006648701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002579798,"about_ca_topic_score_gemma":0.0002804833,"domain_scores_codex":[0.9992538,0.0001620209,0.00004488505,0.0001748873,0.0002599543,0.0001044623],"domain_scores_gemma":[0.9992905,0.0002202183,0.0001362836,0.000195304,0.00009341774,0.00006426657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007008534,0.0005135576,0.001503881,0.0003965229,0.0000376785,0.0003826971,0.000469704,0.0177222,0.924217,0.04193566,0.0007947217,0.01132549],"study_design_scores_gemma":[0.000120289,0.0009877748,0.0005161767,0.00001313681,0.0000200866,0.0000712754,0.00004268149,0.04065346,0.9534522,0.001758452,0.002331939,0.00003250095],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9428173,0.0001066294,0.05215951,0.0002628926,0.00004827476,0.000240949,0.0001829074,0.0004275955,0.003753821],"genre_scores_gemma":[0.9426814,0.00010177,0.05591132,0.00006243614,0.00001222548,0.0002265362,0.00007873257,0.00005292352,0.0008725917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00222125,"threshold_uncertainty_score":0.007430851,"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."}}