{"id":"W2110607426","doi":"10.26421/qic11.5-6-10","title":"Assisted entanglement distillation","year":2011,"lang":"en","type":"preprint","venue":"Quantum Information and Computation","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute; McGill University","funders":"Office of Naval Research; Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Research Chairs; Canadian Institute for Advanced Research","keywords":"Quantum entanglement; Entanglement distillation; Computer science; Distillation; Alice and Bob; Quantum; Theoretical computer science; Squashed entanglement; Alice (programming language); Quantum mechanics; Physics; Chemistry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003999135,0.000315219,0.0002798451,0.0006057663,0.0002277388,0.000861751,0.000437761,0.0002328364,0.00003031011],"category_scores_gemma":[0.00002570478,0.0003123614,0.0001249609,0.0003482873,0.00005295042,0.002693824,0.000549713,0.0003175911,0.0001585298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000721667,"about_ca_system_score_gemma":0.0001177915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000498582,"about_ca_topic_score_gemma":0.000003214138,"domain_scores_codex":[0.9979283,0.0000816558,0.0009920102,0.0002704423,0.0004834614,0.0002441156],"domain_scores_gemma":[0.9982057,0.00003970929,0.0008756205,0.0004016535,0.0003296253,0.0001476486],"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":[0.00001782844,0.00005054636,0.0001781667,0.0002824551,0.00005222577,9.088873e-7,0.00591414,0.001275619,0.000006497958,0.7073708,0.002226496,0.2826243],"study_design_scores_gemma":[0.0005804489,0.0001014633,0.01940345,0.00009645984,0.00002366412,0.00002038464,0.0002856474,0.8782697,0.000066023,0.09240308,0.008234194,0.0005155229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01848033,0.00009950003,0.9692819,0.0004066936,0.001161816,0.0005249773,0.00002198159,0.0005309227,0.009491877],"genre_scores_gemma":[0.9789579,0.0001231599,0.01921204,0.000837145,0.00004047281,0.00006627261,0.0007457779,0.000008332924,0.000008919454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9604775,"threshold_uncertainty_score":0.9999328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02878367295185291,"score_gpt":0.2609187013709399,"score_spread":0.232135028419087,"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."}}