{"id":"W3212683876","doi":"10.1007/978-3-030-92548-2_8","title":"GMMT: A Revocable Group Merkle Multi-tree Signature Scheme","year":2021,"lang":"en","type":"preprint","venue":"Lecture notes in computer science","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Merkle tree; Group signature; Computer science; Scheme (mathematics); Tree (set theory); Group (periodic table); Computer security; Ring signature; Computer network; Digital signature; Mathematics; Cryptography; Hash function; Public-key cryptography; Combinatorics; Cryptographic hash function; Physics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science","research_integrity"],"consensus_categories":["open_science"],"category_scores_codex":[0.001653932,0.0007410764,0.000786651,0.0008890027,0.0004386099,0.002354825,0.008195901,0.0006804488,0.00002656571],"category_scores_gemma":[0.0003485291,0.0007077988,0.0003435384,0.00458195,0.0006796218,0.001475093,0.01203441,0.002712962,0.00001403062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002239066,"about_ca_system_score_gemma":0.0008681044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003566644,"about_ca_topic_score_gemma":0.001136986,"domain_scores_codex":[0.9932047,0.0002340897,0.0006675266,0.003333171,0.001335003,0.001225545],"domain_scores_gemma":[0.9946455,0.0004073431,0.0003341671,0.003873156,0.0003952504,0.000344527],"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":[0.00002535302,0.001459779,0.005485706,0.000687468,0.00009738626,0.0009458701,0.009378486,0.06668444,0.009887226,0.009717566,0.0002556654,0.8953751],"study_design_scores_gemma":[0.0005503912,0.0001116201,0.003577068,0.0006438132,0.00001088266,0.0000669085,0.000002806638,0.9578903,0.006282111,0.02931194,0.0004225258,0.001129586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009442334,0.003785327,0.9809178,0.0008757662,0.004029571,0.00054197,0.00002672876,0.000352113,0.00002838459],"genre_scores_gemma":[0.3636517,0.00006545574,0.6347298,0.001197697,0.0002594734,0.00003257023,0.00004663231,0.0000162886,3.935708e-7],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8942454,"threshold_uncertainty_score":0.9995878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01833215298826052,"score_gpt":0.2630940119958617,"score_spread":0.2447618590076012,"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."}}