{"id":"W2963526330","doi":"10.4230/lipics.tqc.2019.2","title":"Quantum Distinguishing Complexity, Zero-Error Algorithms, and Statistical Zero Knowledge","year":2019,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bounded function; Zero (linguistics); Mathematics; Measure (data warehouse); Discrete mathematics; Function (biology); Upper and lower bounds; State (computer science); Boolean function; Algorithm; Combinatorics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008595063,0.0004778257,0.0006145989,0.0002700888,0.0004765337,0.001041318,0.001459692,0.0002096943,0.0000375665],"category_scores_gemma":[0.0001908367,0.0004411046,0.0001818063,0.0004226703,0.0003053553,0.002218561,0.001412811,0.0005630223,0.0002314977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006891806,"about_ca_system_score_gemma":0.00008589267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005740601,"about_ca_topic_score_gemma":0.00002615302,"domain_scores_codex":[0.9968859,0.00007218241,0.001055119,0.0005283622,0.0005130681,0.00094538],"domain_scores_gemma":[0.9974182,0.0004711159,0.0003573307,0.001076688,0.0002748264,0.0004018263],"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":[0.00006269093,0.0004420251,0.01262091,0.0009783288,0.0001147139,0.000009064243,0.009646056,0.000009088418,0.00002454459,0.9494124,0.0105,0.0161802],"study_design_scores_gemma":[0.00544861,0.0007884934,0.01500012,0.0003884005,0.00007079683,0.0001965059,0.001030811,0.6877196,0.0001201919,0.1338427,0.1537234,0.001670442],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08179524,0.0001271163,0.9095252,0.0001689206,0.001481089,0.0009789284,0.002074143,0.0003254129,0.003524024],"genre_scores_gemma":[0.8399231,0.00002639055,0.1583544,0.0004886107,0.0001136093,0.00004484611,0.0009689749,0.00003840696,0.00004158348],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8155697,"threshold_uncertainty_score":0.9999957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03387183656975885,"score_gpt":0.2957106843187253,"score_spread":0.2618388477489665,"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."}}