{"id":"W2950407838","doi":"10.1145/3312741","title":"Nonhomogeneous Place-dependent Markov Chains, Unsynchronised AIMD, and Optimisation","year":2019,"lang":"en","type":"article","venue":"Journal of the ACM","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"FP7 Ideas: European Research Council; Science Foundation Ireland","keywords":"Markov chain; Constraint (computer-aided design); Mathematical optimization; Convergence (economics); Computer science; Markov process; Resource (disambiguation); Key (lock); Class (philosophy); Mathematics; Artificial intelligence; Machine learning; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006994247,0.0001086443,0.0001916928,0.0001334466,0.0001144057,0.0001167361,0.0007400074,0.00004106223,0.0002081825],"category_scores_gemma":[0.0005931729,0.00007222503,0.0001191425,0.0001722548,0.00003102376,0.0005604865,0.0004544716,0.000170096,0.00005839749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000603857,"about_ca_system_score_gemma":0.00001991988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001121831,"about_ca_topic_score_gemma":0.0000100085,"domain_scores_codex":[0.9991747,0.00002734009,0.000271727,0.0001098106,0.0002791544,0.000137342],"domain_scores_gemma":[0.9986027,0.00008599541,0.0006282491,0.0005471705,0.0001239918,0.00001183491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003718863,0.0006890948,0.1349281,0.00106292,0.002134788,0.0002826704,0.001046215,0.6039093,0.1106705,0.01799066,0.02470724,0.0988597],"study_design_scores_gemma":[0.02689188,0.0005668661,0.06102198,0.002582192,0.005498962,0.001707474,0.006035498,0.2868803,0.01770221,0.351225,0.2356364,0.004251168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937086,0.0002336699,0.000368288,0.003668122,0.0005155738,0.0001152241,5.64689e-7,0.00001479037,0.001375233],"genre_scores_gemma":[0.9958869,0.00003696282,0.0008931,0.0009255912,0.0006546302,7.345092e-7,6.946469e-7,0.00001782753,0.001583606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3332344,"threshold_uncertainty_score":0.2945251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007230562928702009,"score_gpt":0.2096683075004045,"score_spread":0.2024377445717025,"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."}}