{"id":"W2889233420","doi":"10.1155/2018/7462439","title":"A Note on the Waiting-Time Distribution in an Infinite-Buffer <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\"><mml:mi>G</mml:mi><mml:msup><mml:mrow><mml:mi>I</mml:mi></mml:mrow><mml:mrow><mml:mo stretchy=\"false\">[</mml:mo><mml:mi>X</mml:mi><mml:mo stretchy=\"false\">]</mml:mo></mml:mrow></mml:msup><mml:mo>/</mml:mo><mml:mi>C</mml:mi><mml:mtext>-</mml:mtext><mml:mi>M</mml:mi><mml:mi>S</mml:mi><mml:mi>P</mml:mi><mml:mo>/</mml:mo><mml:mn fontstyle=\"italic\">1</mml:mn></mml:math> Queueing System","year":2018,"lang":"en","type":"article","venue":"Journal of Probability and Statistics","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Armed Forces; Royal Military College of Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Algorithm; Markovian arrival process; Computer science; Function (biology); Distribution (mathematics); Mathematics; Markov chain; Machine learning; Mathematical analysis","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":[0.003667426,0.001099512,0.0009143972,0.0009259869,0.0007928541,0.002169142,0.002816472,0.0008900525,0.00629836],"category_scores_gemma":[0.01300438,0.000677467,0.0007667036,0.002374252,0.001951392,0.005271039,0.001407127,0.003743764,0.001504437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003153729,"about_ca_system_score_gemma":0.002277888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01208005,"about_ca_topic_score_gemma":0.004116144,"domain_scores_codex":[0.9985293,0.0003999235,0.00008492578,0.0002617076,0.0005632883,0.000160906],"domain_scores_gemma":[0.9938445,0.004206841,0.0002853625,0.0004856742,0.0008758463,0.0003017146],"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":[0.0002963003,0.00009637939,0.0009521326,0.0002720805,0.00004303518,0.0007187256,0.0004350148,0.0891768,0.003633044,0.8559239,0.01925207,0.02920042],"study_design_scores_gemma":[0.00004556113,0.0001371776,0.001019883,0.0001074241,0.0000443291,0.0003003526,0.0001011716,0.6486946,0.002130017,0.3218781,0.02546707,0.00007418349],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01849489,0.005521924,0.947384,0.00333697,0.001451557,0.00005174237,0.0004239483,0.0005665491,0.02276834],"genre_scores_gemma":[0.767313,0.01290221,0.1427954,0.002149529,0.00480628,0.0002269972,0.0008474983,0.001051553,0.06790752],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01208005,"threshold_uncertainty_score":0.02401948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01758962478789432,"score_gpt":0.2405340387255108,"score_spread":0.2229444139376164,"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."}}