{"id":"W2577487606","doi":"","title":"Faster individual discrete logarithms in non-prime finite fields with the NFS and FFS algorithms","year":2016,"lang":"en","type":"preprint","venue":"IACR Cryptology ePrint Archive","topic":"Cryptography and Residue Arithmetic","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Institute for the Mathematical Sciences; University of Calgary","funders":"","keywords":"Finite field; Discrete logarithm; Mathematics; Algorithm; Logarithm; Polynomial; Exponent; Field (mathematics); Discrete mathematics; Computer science; Pure mathematics; Mathematical analysis; Encryption","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001574082,0.0009827605,0.001114067,0.001770774,0.0006194329,0.002325736,0.001260583,0.0006753011,0.009104431],"category_scores_gemma":[0.006482033,0.0004038498,0.001681042,0.001533504,0.001222918,0.007176664,0.002657842,0.002294103,0.004671167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001388727,"about_ca_system_score_gemma":0.001764137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001875877,"about_ca_topic_score_gemma":0.002358149,"domain_scores_codex":[0.9978915,0.000369297,0.0001655401,0.0003869964,0.0009349274,0.0002517134],"domain_scores_gemma":[0.9970885,0.001048118,0.0001605974,0.001290758,0.0003089627,0.000103119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008588693,0.0003211416,0.00298276,0.0003641646,0.00008640335,0.0001932426,0.0004872383,0.04127043,0.01289622,0.2380392,0.0134111,0.6890891],"study_design_scores_gemma":[0.0002692566,0.0003202206,0.001175109,0.0001289228,0.00007789284,0.0005271612,0.0001646375,0.4415794,0.028092,0.4970919,0.0304895,0.0000839295],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05542299,0.000743953,0.9229378,0.0006957705,0.0001785781,0.0001321179,0.0002757841,0.005573712,0.01403926],"genre_scores_gemma":[0.3279902,0.0005167574,0.651507,0.0003314878,0.0003729994,0.000197681,0.001316324,0.0008601658,0.01690746],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009104431,"threshold_uncertainty_score":0.03045738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01075818428019135,"score_gpt":0.2394017570258224,"score_spread":0.228643572745631,"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."}}