{"id":"W4366580988","doi":"10.1038/s41598-023-32461-3","title":"Optimization of the multivariate polynomial public key for quantum safe digital signature","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Quantropi (Canada)","funders":"","keywords":"Univariate; Polynomial; Public-key cryptography; Mathematics; Key (lock); Discrete mathematics; Multivariate statistics; Computer science; Encryption; Statistics; Computer security; Mathematical analysis","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":[0.0009965808,0.00008627453,0.0001042034,0.0002357801,0.0004915603,0.0007844917,0.000447429,0.00004587427,0.00001606256],"category_scores_gemma":[0.0002854323,0.00006248719,0.0001457803,0.002023703,0.0001315791,0.0006554637,0.0002580364,0.00006126527,0.000002326172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001721672,"about_ca_system_score_gemma":0.0001891902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001296796,"about_ca_topic_score_gemma":0.0000119496,"domain_scores_codex":[0.9984391,0.00002812446,0.0004024407,0.0004562196,0.0004122177,0.0002619316],"domain_scores_gemma":[0.9985076,0.00007083874,0.0003047799,0.0007951048,0.0002651722,0.00005650922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004429916,0.0009708072,0.0238438,0.0002335108,0.0002589296,0.0001110887,0.01836721,0.06389673,0.03824298,0.2854856,0.5131969,0.05534814],"study_design_scores_gemma":[0.000670378,0.00006937564,0.006927267,0.00003394197,0.00001820151,0.00005778432,0.0003865889,0.8047068,0.005054087,0.05482513,0.1268448,0.0004057016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1867791,0.00003490493,0.7904911,0.003124894,0.01759443,0.001168418,0.00006421507,0.0002493815,0.0004935843],"genre_scores_gemma":[0.9937208,7.305496e-7,0.005738551,0.00001994252,0.00003562191,0.00002692837,0.00009656616,0.000006228012,0.0003546546],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8069417,"threshold_uncertainty_score":0.7564871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02618080632098485,"score_gpt":0.2731052661847381,"score_spread":0.2469244598637532,"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."}}