{"id":"W2252673298","doi":"10.1080/00207179.2016.1146968","title":"<i>r</i>-extreme signalling for congestion control","year":2016,"lang":"en","type":"article","venue":"International Journal of Control","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Science Foundation Ireland; European Commission","keywords":"Interval (graph theory); Network congestion; Maxima; Maxima and minima; Resource (disambiguation); Population; Computer science; Scalar (mathematics); Instant; Control (management); Operations research; Econometrics; Mathematics; Computer network; Combinatorics; Demography; Biology; Sociology; Artificial intelligence; History","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":[0.002180843,0.0005495528,0.000672656,0.0006247355,0.0007359329,0.001568577,0.001345875,0.001649577,0.004764344],"category_scores_gemma":[0.009972792,0.0002643482,0.0006898423,0.0007092124,0.002422294,0.002086962,0.00185517,0.003148232,0.0009177445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001404473,"about_ca_system_score_gemma":0.000739296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001503972,"about_ca_topic_score_gemma":0.001071938,"domain_scores_codex":[0.9988995,0.0004842698,0.00004668896,0.0001706955,0.0002564585,0.0001423921],"domain_scores_gemma":[0.9964458,0.002289635,0.0004482252,0.0003534418,0.0003055035,0.0001574248],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007671187,0.00003347885,0.0002266912,0.0000732772,0.00001585979,0.0001029729,0.0001012355,0.08809385,0.002514436,0.8878644,0.003724984,0.01717214],"study_design_scores_gemma":[0.00001301899,0.00005018974,0.0001813839,0.00003513372,0.000008578611,0.0001043238,0.00002247872,0.5996567,0.0006145003,0.3948383,0.004448652,0.00002689355],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01075775,0.0009845421,0.9649752,0.001700604,0.0002781309,0.00003631313,0.0000615195,0.0002561507,0.02094965],"genre_scores_gemma":[0.8849053,0.001523228,0.0981744,0.001273602,0.0006858429,0.0001729643,0.0000847498,0.0001392421,0.01304066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004764344,"threshold_uncertainty_score":0.01593834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.015878293528881,"score_gpt":0.2446114727377989,"score_spread":0.2287331792089179,"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."}}