{"id":"W3046463707","doi":"10.1145/3382734.3405736","title":"Recoverable Mutual Exclusion with Constant Amortized RMR Complexity from Standard Primitives","year":2020,"lang":"en","type":"article","venue":"","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mutual exclusion; Computer science; Process (computing); Crash; Constant (computer programming); Protocol (science); Shared memory; Theoretical computer science; Distributed computing; Parallel computing; Programming language","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":[0.002707998,0.001624662,0.002100446,0.001433355,0.001538202,0.004014003,0.004193874,0.00239395,0.01306508],"category_scores_gemma":[0.01404698,0.0006017094,0.002261715,0.001661986,0.003105738,0.01152008,0.008404227,0.006460095,0.003133429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003126625,"about_ca_system_score_gemma":0.003146184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009428899,"about_ca_topic_score_gemma":0.001166172,"domain_scores_codex":[0.9951381,0.000841158,0.0002561204,0.0008058331,0.001973114,0.0009856855],"domain_scores_gemma":[0.9866918,0.007178646,0.0007815939,0.004215356,0.0006357096,0.0004968388],"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":[0.0006948655,0.0002210571,0.0003746634,0.0004114004,0.00007584432,0.0002503344,0.0002494519,0.0854019,0.008374446,0.846476,0.009643204,0.04782686],"study_design_scores_gemma":[0.0001126634,0.00007366808,0.0001284651,0.00003217394,0.00003425557,0.0001512947,0.00002297314,0.2484329,0.002787008,0.7445549,0.003630283,0.00003940105],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05216506,0.001104818,0.9019923,0.003320118,0.0002176798,0.0003110641,0.0006919096,0.003981097,0.03621588],"genre_scores_gemma":[0.704392,0.0008260534,0.2769165,0.00076259,0.0005955905,0.0009856764,0.001054514,0.0009017457,0.01356546],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01306508,"threshold_uncertainty_score":0.04370701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03569281660777281,"score_gpt":0.2341445985202507,"score_spread":0.1984517819124779,"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."}}