{"id":"W3043468564","doi":"10.1103/physrevresearch.2.043172","title":"Improving key rates of the unbalanced phase-encoded BB84 protocol using the flag-state squashing model","year":2020,"lang":"en","type":"article","venue":"Physical Review Research","topic":"Physical Unclonable Functions (PUFs) and Hardware Security","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo; Huawei Technologies; Western Canada Research Grid; Industry Canada; Compute Canada","keywords":"Key (lock); Mathematical proof; Exploit; Protocol (science); BB84; SIGNAL (programming language); A priori and a posteriori","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":[0.001310216,0.0002127267,0.0004744586,0.00003605576,0.0006564707,0.0002031187,0.002363119,0.00002645276,0.000008181001],"category_scores_gemma":[0.001159948,0.0001138001,0.0003084256,0.00225823,0.0002835782,0.0005937158,0.001434956,0.001044142,0.00003252749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007989731,"about_ca_system_score_gemma":0.0004263586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007077974,"about_ca_topic_score_gemma":0.000003954793,"domain_scores_codex":[0.996232,0.0008414566,0.0004122849,0.0005782729,0.00131701,0.000619002],"domain_scores_gemma":[0.9974971,0.0004993549,0.0001950747,0.001022441,0.0005850833,0.0002008862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000335827,0.003355144,0.00006544657,0.01753743,0.0002027071,0.00002011079,0.008358731,0.01528875,0.5481887,0.202293,0.008101543,0.1962526],"study_design_scores_gemma":[0.0004152851,0.000148963,0.000006526088,0.0007665801,0.00001353108,9.13224e-7,0.00001566709,0.9544581,0.02485459,0.01602636,0.00315,0.0001434967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03861267,0.002660964,0.7808055,0.0379815,0.0002388931,0.1343373,0.00007615668,0.0004042089,0.004882747],"genre_scores_gemma":[0.9818714,0.0001915368,0.002036745,0.001544646,0.0004753202,0.01377942,0.000002249133,0.00003645273,0.000062224],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9432588,"threshold_uncertainty_score":0.5049108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2003563624206547,"score_gpt":0.4729712018670892,"score_spread":0.2726148394464345,"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."}}