{"id":"W2984654445","doi":"10.1049/iet-ifs.2018.5288","title":"Choosing subfields for LUOV and lifting fields for rainbow","year":2019,"lang":"en","type":"article","venue":"IET Information Security","topic":"Polynomial and algebraic computation","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University of Edmonton","funders":"Viet Nam National University Ho Chi Minh City","keywords":"Rainbow; NIST; Public-key cryptography; Binary number; Cryptography; Signature (topology); Key (lock); Scheme (mathematics); Computer science; Multivariate statistics; Field (mathematics); Mathematics; Theoretical computer science; Algorithm; Arithmetic; Computer security; Statistics; Speech recognition; Physics; Optics; Encryption; Pure mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002983027,0.00007354288,0.00009709701,0.00006161683,0.0001171176,0.0002312062,0.0001661054,0.000070312,0.000004314944],"category_scores_gemma":[0.00007691151,0.00007143582,0.00004655856,0.0000883948,0.000008004015,0.001779038,0.00007211616,0.00006327043,0.00001226525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001382911,"about_ca_system_score_gemma":0.00003400733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001215823,"about_ca_topic_score_gemma":0.000002764535,"domain_scores_codex":[0.9994221,0.000008956586,0.0002199544,0.0001040974,0.0000889265,0.0001560161],"domain_scores_gemma":[0.9994186,0.0002041049,0.0001104503,0.00013027,0.00009218423,0.0000443709],"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":[0.00008580008,0.00004243986,0.0009660525,0.0007184948,0.00003699206,1.845084e-7,0.03785392,0.0007419054,0.0001658927,0.3306633,0.01193306,0.6167919],"study_design_scores_gemma":[0.001321475,0.0001690044,0.001279785,0.00003309362,0.00000472238,0.000005875877,0.0002065346,0.8950502,0.00151722,0.04911495,0.05106104,0.000236082],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2302329,0.00002134596,0.7656781,0.001859182,0.0005672877,0.0005210643,0.000009449303,0.00009553964,0.001015135],"genre_scores_gemma":[0.9880334,0.000002750148,0.01047655,0.001320017,0.00008252623,0.00002773456,0.00002119326,0.00000220997,0.00003368082],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8943083,"threshold_uncertainty_score":0.2913068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007333392382511736,"score_gpt":0.2300969670906782,"score_spread":0.2227635747081665,"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."}}