{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"category_scores_codex":[0.009596311,0.003053038,0.001433878,0.00236436,0.006339142,0.00653879,0.006876308,0.006275562,0.2526123],"category_scores_gemma":[0.01030523,0.005657126,0.004969738,0.004629542,0.00594963,0.006350705,0.005622123,0.006316155,0.003546481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001439546,"about_ca_system_score_gemma":0.003842776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006154958,"about_ca_topic_score_gemma":0.007211468,"domain_scores_codex":[0.9708196,0.002262233,0.007128668,0.005282963,0.007576902,0.006929658],"domain_scores_gemma":[0.9746981,0.006462485,0.009094887,0.005500122,0.001368231,0.002876223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005869843,0.001298549,0.0001153088,0.004025083,0.004693723,0.003557944,0.003386437,0.00777226,0.002306462,0.6579763,0.3022746,0.006723503],"study_design_scores_gemma":[0.007269979,0.005776398,0.0002584124,0.005719973,0.00784315,0.004594567,0.008532033,0.03629809,0.8852788,0.0227111,0.008772316,0.006945153],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7567074,0.00261105,0.009163653,0.002500513,0.006834954,0.0002976514,0.002786767,0.001071533,0.2180265],"genre_scores_gemma":[0.9717699,0.001714973,0.006615668,0.003231656,0.006958024,0.002594976,0.004459695,0.002366256,0.0002889133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8829724,"threshold_uncertainty_score":0.9984969,"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."}}