{"id":"W2570310514","doi":"10.1007/s00446-014-0211-x","title":"Randomized distributed decision","year":2014,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Computer science; Boosting (machine learning); Randomized algorithm; Context (archaeology); Monte Carlo method; Randomization; Distributed algorithm; Theoretical computer science; Artificial intelligence; Distributed computing; Algorithm; Randomized controlled trial; Mathematics; 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":[0.006929921,0.001587821,0.00364951,0.001357345,0.002529901,0.004596557,0.004717937,0.003124089,0.02744792],"category_scores_gemma":[0.03100004,0.001033515,0.001633107,0.003039888,0.003290397,0.007898296,0.005018621,0.005014098,0.003577094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004760454,"about_ca_system_score_gemma":0.007504612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002174836,"about_ca_topic_score_gemma":0.003647073,"domain_scores_codex":[0.9876695,0.005445566,0.0004142048,0.003123315,0.001822598,0.00152481],"domain_scores_gemma":[0.9682064,0.02103926,0.001063762,0.006444219,0.001852606,0.001393688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003039698,0.001277253,0.001598465,0.0005762052,0.000222376,0.0001638105,0.0001974523,0.1791439,0.001835035,0.5845543,0.08356836,0.1438231],"study_design_scores_gemma":[0.0004885283,0.0001375148,0.0002391638,0.00003616578,0.00005626721,0.00007371391,0.0000473354,0.5904188,0.0009524744,0.4018513,0.005668465,0.00003024711],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04335401,0.001511974,0.9032078,0.008407327,0.001207006,0.0007767814,0.001665476,0.002039048,0.03783075],"genre_scores_gemma":[0.7315632,0.0008711798,0.2175908,0.002496977,0.001778475,0.001246748,0.002451388,0.0005984562,0.04140281],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02744792,"threshold_uncertainty_score":0.09182239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01455801862158842,"score_gpt":0.2548765614012152,"score_spread":0.2403185427796267,"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."}}