{"id":"W4404920231","doi":"10.1103/physrevresearch.6.043223","title":"Improved decoy-state and flag-state squashing methods","year":2024,"lang":"en","type":"article","venue":"Physical Review Research","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo; Innovation, Science and Economic Development Canada","keywords":"Flag (linear algebra); Decoy; State (computer science); Computer security; Computer science; Mathematics; Medicine; Algorithm; Internal medicine","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":[0.003675141,0.0001312689,0.0002555567,0.0002089754,0.0001847736,0.0007041396,0.0006357828,0.00001582554,0.0000242529],"category_scores_gemma":[0.0003106229,0.00009627874,0.0001409097,0.001732726,0.0001209598,0.0009245453,0.0004736843,0.0005816512,0.000393936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000258633,"about_ca_system_score_gemma":0.00007954848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001386068,"about_ca_topic_score_gemma":0.00000177292,"domain_scores_codex":[0.9977887,0.0005703321,0.0002760921,0.0003767211,0.0005206948,0.0004675208],"domain_scores_gemma":[0.9983171,0.0008021423,0.00003032826,0.0004503653,0.0001728612,0.0002272553],"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":[0.000001660904,0.00002211635,0.000001326993,0.001931984,0.00001650969,0.000006847816,0.0006766208,6.360428e-7,0.001364846,0.09487764,0.001830153,0.8992696],"study_design_scores_gemma":[0.0001104434,0.0001461189,0.00007757259,0.001926831,0.000008492171,0.00001598907,0.00001751152,0.5717298,0.003431494,0.1269917,0.2952934,0.0002506793],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006156642,0.1284564,0.8376632,0.009424449,0.0002940123,0.001023453,0.000006270386,0.0003727309,0.01660284],"genre_scores_gemma":[0.6236353,0.2360328,0.1317597,0.005360967,0.0004701141,0.0007803681,0.00001280705,0.0001013898,0.001846551],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.899019,"threshold_uncertainty_score":0.6790034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07963373264211228,"score_gpt":0.4945745652565525,"score_spread":0.4149408326144402,"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."}}