{"id":"W4307714896","doi":"10.5281/zenodo.7190626","title":"When Is Recoverable Consensus Harder Than Consensus?","year":2022,"lang":"en","type":"paratext","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Hellenic Foundation for Research and Innovation; Agence Nationale de la Recherche","keywords":"Consensus algorithm; Computer science; Uniform consensus; Consensus; Artificial intelligence; Data science; Multi-agent system","routes":{"ca_aff":true,"ca_fund":true,"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","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009917546,0.0003977603,0.0004943205,0.0003241613,0.00343776,0.00264748,0.00379658,0.0002170813,0.1288817],"category_scores_gemma":[0.0002669375,0.0004409706,0.0001733253,0.000778206,0.0001792726,0.0001777006,0.003470259,0.0009236645,0.1035224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003742328,"about_ca_system_score_gemma":0.00003942817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001205835,"about_ca_topic_score_gemma":4.302743e-7,"domain_scores_codex":[0.9956591,0.0008781681,0.000595626,0.001209448,0.0009093324,0.0007483879],"domain_scores_gemma":[0.9967225,0.00006931131,0.0004215798,0.001617544,0.0008751482,0.0002939767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000025945,0.00008550865,2.196432e-7,0.0001336013,0.00009670822,0.00005042111,0.001069755,0.0000893965,0.0001550792,0.001726921,0.9791162,0.01745026],"study_design_scores_gemma":[0.0005454571,0.0001857734,0.000008050389,0.00008635663,0.00001217176,0.0003417664,0.0001367452,0.001844682,0.00007729228,0.0002809749,0.9959906,0.0004901104],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003174373,0.001327873,0.02110996,0.005402387,0.002888647,0.001228889,0.00712572,0.001203303,0.9593958],"genre_scores_gemma":[0.02765034,0.0008227921,0.003903797,0.003209239,0.001268195,0.000001155269,0.01872265,0.005971454,0.9384504],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.0273329,"threshold_uncertainty_score":0.9998042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03777083501519694,"score_gpt":0.251176972656189,"score_spread":0.2134061376409921,"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."}}