{"id":"W2005304136","doi":"10.1007/s00224-013-9448-1","title":"Tight Bounds for Adopt-Commit Objects","year":2013,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Commit; Upper and lower bounds; Binary logarithm; Combinatorics; Log-log plot; Matching (statistics); Mathematics; Deterministic algorithm; Discrete mathematics; Class (philosophy); Computer science; Statistics; Database","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":[0.01917101,0.004010202,0.00625254,0.005788418,0.007660802,0.01814042,0.01242842,0.00619735,0.02218757],"category_scores_gemma":[0.1340762,0.003640142,0.002909951,0.008608595,0.008486587,0.04554308,0.02019237,0.01849109,0.00474192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007633778,"about_ca_system_score_gemma":0.008747517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004453254,"about_ca_topic_score_gemma":0.005820249,"domain_scores_codex":[0.9724069,0.005137572,0.001399202,0.00297157,0.01043991,0.007645009],"domain_scores_gemma":[0.7899123,0.130809,0.007236492,0.04898118,0.01446053,0.008600454],"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":[0.002551729,0.0005483066,0.002933694,0.0006987946,0.0001726304,0.0002239097,0.001368137,0.06070402,0.003231699,0.8368468,0.02586702,0.06485341],"study_design_scores_gemma":[0.0001365273,0.0001526651,0.0005335953,0.0001418932,0.0001859915,0.0001401175,0.0002869155,0.1270786,0.002548655,0.8601403,0.008586924,0.00006788156],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08127271,0.008339074,0.8253571,0.01152322,0.001331613,0.00042635,0.001560846,0.005046725,0.06514242],"genre_scores_gemma":[0.8036525,0.004203445,0.1454614,0.00340889,0.00242387,0.001127987,0.002425373,0.004396099,0.03290052],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02218757,"threshold_uncertainty_score":0.1013872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01309922025277097,"score_gpt":0.2289366031529144,"score_spread":0.2158373829001435,"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."}}