{"id":"W2760385998","doi":"10.1103/physrevlett.119.120505","title":"Contextuality as a Resource for Models of Quantum Computation with Qubits","year":2017,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; H2020 European Research Council; Institute for Quantum Information and Matter, California Institute of Technology; Horizon 2020 Framework Programme; Canadian Institute for Advanced Research; Gordon and Betty Moore Foundation; National Science Foundation","keywords":"Kochen–Specker theorem; Quantum computer; Qubit; Cluster state; Computer science; MAGIC (telescope); Computation; Quantum mechanics; Quantum error correction; Quantum; Quantum operation; Theoretical physics; Physics; Theoretical computer science; Open quantum system; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002561981,0.0001105104,0.0003011972,0.00002894852,0.0001592481,0.00009125835,0.0006363544,0.000006804708,8.357335e-7],"category_scores_gemma":[0.00005060777,0.00008166164,0.0001560775,0.00009533449,0.0001159593,0.0007545674,0.00006995082,0.00006427492,0.00001166513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008293281,"about_ca_system_score_gemma":0.00002157473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002174421,"about_ca_topic_score_gemma":7.518933e-7,"domain_scores_codex":[0.9991084,0.0000471662,0.0002422059,0.0001824954,0.000269558,0.0001501785],"domain_scores_gemma":[0.9987689,0.0001129406,0.0004061191,0.0005430943,0.0001048237,0.00006416236],"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":[0.00003079436,0.0001398558,0.00003622255,0.001446274,0.00004686734,0.00000113509,0.0007063038,0.001049131,0.0004108799,0.9668455,0.006962222,0.02232489],"study_design_scores_gemma":[0.0008845296,0.0002503312,0.0008806371,0.001538892,0.00004539767,0.000004716966,0.00001922921,0.956835,0.000389293,0.03043333,0.008413101,0.0003055067],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05435567,0.0003157352,0.9339655,0.009979692,0.00002732769,0.0004899274,0.000004863504,0.00004525068,0.0008160258],"genre_scores_gemma":[0.9838681,0.00009143325,0.003289163,0.01266606,0.00002532155,0.00004704794,0.000005608676,0.000005440362,0.000001778805],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9557859,"threshold_uncertainty_score":0.3330065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04152252576280158,"score_gpt":0.327234600313672,"score_spread":0.2857120745508704,"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."}}