{"id":"W1977809545","doi":"10.1007/s11009-007-9036-4","title":"Multiple Eigenvalues in Spectral Analysis for Solving QBD Processes","year":2007,"lang":"en","type":"article","venue":"Methodology And Computing In Applied Probability","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Eigenvalues and eigenvectors; Context (archaeology); Queueing theory; Applied mathematics; Birth–death process; Mathematical optimization; Statistics; Population","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":[0.0121348,0.0002090691,0.000610958,0.0006183087,0.0001842477,0.00004902639,0.0002086371,0.0001388269,0.00001505905],"category_scores_gemma":[0.002490757,0.0002073967,0.00009629162,0.001973889,0.0001739069,0.0001425281,0.0001704513,0.0002423947,0.000002004075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005887861,"about_ca_system_score_gemma":0.00001667127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002130816,"about_ca_topic_score_gemma":0.003661883,"domain_scores_codex":[0.9980395,0.00009043173,0.0005991831,0.0006656183,0.00009527615,0.0005100252],"domain_scores_gemma":[0.9954388,0.00396273,0.0002585431,0.00024417,0.00008157008,0.0000142586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005555382,0.000164252,0.8293616,0.0005747785,0.0001252162,0.000003723637,0.0005627522,0.117606,0.0004031848,0.03546196,0.000002213436,0.01517877],"study_design_scores_gemma":[0.0009283588,0.00001219242,0.2725995,0.0000263506,0.0002710808,9.152312e-7,0.0007292542,0.1219895,0.0008017381,0.6020551,0.0001883422,0.0003976194],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5708114,0.00006604461,0.4282521,0.00005033832,0.00003830785,0.0003130538,4.780024e-7,0.0000629059,0.0004054423],"genre_scores_gemma":[0.8324801,0.00000210984,0.1670366,0.0002478565,0.0001676886,0.0000348575,0.00001396066,0.00001205285,0.000004737407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5665932,"threshold_uncertainty_score":0.8457392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08094399951014415,"score_gpt":0.3214438958120218,"score_spread":0.2404998963018777,"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."}}