{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006081392,0.000751831,0.002364755,0.001116075,0.00201702,0.004238527,0.002622725,0.00650917,0.008837985],"category_scores_gemma":[0.06759626,0.001055328,0.001454311,0.001815874,0.004840476,0.01611195,0.003848021,0.005345902,0.0009110008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001175455,"about_ca_system_score_gemma":0.00101976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001488973,"about_ca_topic_score_gemma":0.0008351651,"domain_scores_codex":[0.9918926,0.002500952,0.0004241503,0.001837708,0.001550129,0.001794427],"domain_scores_gemma":[0.9098148,0.07380297,0.005580004,0.006115464,0.002450415,0.00223644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002830532,0.0009186553,0.01493376,0.002132249,0.0007716673,0.002195908,0.003340724,0.4510754,0.01563466,0.3430889,0.02960889,0.1334686],"study_design_scores_gemma":[0.0002797965,0.0002586156,0.001843491,0.00008208402,0.00007956191,0.0008337027,0.001590439,0.3560452,0.004899188,0.6300737,0.003930327,0.00008395458],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5861539,0.002594129,0.3604477,0.02824302,0.0006065422,0.0002527792,0.0005593879,0.001331917,0.01981064],"genre_scores_gemma":[0.9592001,0.0008619193,0.03380885,0.0009381528,0.0006320296,0.0002074068,0.0004017925,0.000315229,0.003634638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008837985,"threshold_uncertainty_score":0.03216183,"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."}}