{"id":"W3183901574","doi":"10.1145/3465084.3467938","title":"Tight Lower Bound for the RMR Complexity of Recoverable Mutual Exclusion","year":2021,"lang":"en","type":"article","venue":"","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canada Research Chairs","keywords":"Mutual exclusion; Swap (finance); Upper and lower bounds; Fetch; Computer science; Synchronization (alternating current); Log-log plot; Algorithm; Binary logarithm; Parallel computing; Combinatorics; Mathematics; Theoretical computer science; Topology (electrical circuits)","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":[],"consensus_categories":[],"category_scores_codex":[0.0002674784,0.00007470355,0.0001487409,0.00001141087,0.0001920584,0.0001155922,0.000469535,0.00003732713,0.0001254668],"category_scores_gemma":[0.00003850929,0.00004800807,0.00009233184,0.0002134209,0.00005871414,0.0001877161,0.0001921375,0.00005198181,0.00001932398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001889823,"about_ca_system_score_gemma":0.00008880803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007904405,"about_ca_topic_score_gemma":0.0001079044,"domain_scores_codex":[0.9991716,0.00003339762,0.0002116668,0.0002268972,0.0001866807,0.0001698165],"domain_scores_gemma":[0.9989906,0.0001627798,0.00006970441,0.0005313514,0.0002097104,0.00003586113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003598788,0.000292548,0.0001818472,0.00008454351,0.0000643227,0.00001467993,0.000499477,0.0002683209,0.005589273,0.833216,0.1374584,0.02229457],"study_design_scores_gemma":[0.0008686559,0.0001250277,0.001899852,0.00005899778,0.000009822426,0.00002854569,0.0001091098,0.2153956,0.01519994,0.01780157,0.7482689,0.0002340032],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007135973,0.000381181,0.9762845,0.002318063,0.00105697,0.0001853962,0.00003935849,0.00004066584,0.01255791],"genre_scores_gemma":[0.966162,0.00002261325,0.02006605,0.0005911228,0.0001120669,0.00002024568,0.00001505665,0.000006338775,0.01300455],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.959026,"threshold_uncertainty_score":0.1957712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04479827334313959,"score_gpt":0.2708985467195957,"score_spread":0.2261002733764561,"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."}}