{"id":"W1713951430","doi":"10.1007/978-3-540-27796-5_22","title":"Optimal Decision Strategies in Byzantine Environments","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Correctness; Computer science; Probability distribution; Expected value; Optimal decision; Set (abstract data type); Mathematical optimization; Markov decision process; Value (mathematics); Decision rule; Decision problem; Mathematics; Algorithm; Decision tree; Artificial intelligence; Markov process; Machine learning; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00159408,0.0008868792,0.001125464,0.0006298675,0.0008257208,0.002918664,0.001165317,0.00134803,0.004641934],"category_scores_gemma":[0.006314975,0.0004986397,0.0003590103,0.001014224,0.001234485,0.003850181,0.00168503,0.001648863,0.0006815617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009971861,"about_ca_system_score_gemma":0.0008967431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009930634,"about_ca_topic_score_gemma":0.001422907,"domain_scores_codex":[0.9985768,0.0007816014,0.00006149001,0.0001488691,0.0001793823,0.0002518634],"domain_scores_gemma":[0.9973911,0.00199853,0.0001605997,0.0001567271,0.0001467788,0.0001462254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005038303,0.00008868866,0.0002847773,0.000192597,0.00003992257,0.0001083108,0.0004088134,0.197491,0.00220924,0.7214961,0.004355269,0.07282143],"study_design_scores_gemma":[0.00007710985,0.0000830345,0.00008409834,0.00002278491,0.00001680727,0.00004209196,0.00009548029,0.3511553,0.001226522,0.6441327,0.003048284,0.00001591032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1401722,0.0009331784,0.8184115,0.001230699,0.00008659055,0.0001445649,0.0001766808,0.0004406461,0.03840394],"genre_scores_gemma":[0.7990749,0.0009724998,0.1820067,0.0001541524,0.00006791069,0.0001842585,0.0001473926,0.0001773907,0.01721482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004641934,"threshold_uncertainty_score":0.0155288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01087631704067274,"score_gpt":0.2384796948626427,"score_spread":0.22760337782197,"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."}}