{"id":"W4281621365","doi":"10.1145/3519270.3538418","title":"When is Recoverable Consensus Harder Than Consensus?","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Hellenic Foundation for Research and Innovation; Agence Nationale de la Recherche","keywords":"Consensus; Computer science; Uniform consensus; Object (grammar); Class (philosophy); Focus (optics); Consensus algorithm; Consensus conference; Crash; Distributed computing; Multi-agent system; Artificial intelligence; Algorithm","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006643767,0.0004631986,0.0006752816,0.0001299222,0.0002940735,0.0006881537,0.002151078,0.0003003124,0.002584447],"category_scores_gemma":[0.0000561006,0.0004496126,0.0003188319,0.0002202843,0.00007445832,0.00006504641,0.003099354,0.0009694142,0.0003388892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001860054,"about_ca_system_score_gemma":0.0005788581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001748113,"about_ca_topic_score_gemma":0.00005595686,"domain_scores_codex":[0.9963657,0.0002541655,0.0006901223,0.001390859,0.0007088225,0.000590314],"domain_scores_gemma":[0.9966334,0.0001780228,0.0003927178,0.002356838,0.0002383624,0.0002006755],"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":[0.00001382695,0.0001003622,0.0005590229,0.0001830998,0.0001750561,0.0001723468,0.001422167,0.0007575472,0.00004548694,0.01677536,0.9763614,0.00343431],"study_design_scores_gemma":[0.0006226815,0.00006312185,0.0003339546,0.0001391188,0.0000205108,0.0001089875,0.0001957883,0.06059481,0.0002215929,0.03525584,0.9014072,0.001036418],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03286642,0.00415086,0.3094442,0.05612979,0.024164,0.003570511,0.003334426,0.002915976,0.5634238],"genre_scores_gemma":[0.5592453,0.0001690571,0.1386266,0.01158647,0.0007242819,0.0007225859,0.0003730296,0.0001539884,0.2883986],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5263789,"threshold_uncertainty_score":0.9997956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03078858875991975,"score_gpt":0.2649005089795085,"score_spread":0.2341119202195888,"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."}}