{"id":"W2012309514","doi":"10.1016/j.ejor.2006.09.086","title":"Applications of bulk queues to group testing models with incomplete identification","year":2006,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":76,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Poisson distribution; Mathematical optimization; Queue; Markov chain; Population; Computer science; Markov decision process; Profit (economics); Random variable; Mathematics; Group (periodic table); Markov process; Statistics","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":[0.003019335,0.0000767103,0.0001518655,0.0004804495,0.0002114295,0.00007935917,0.0001659825,0.00001344786,0.00001366706],"category_scores_gemma":[0.0006683251,0.00006053804,0.0000390042,0.0008088974,0.00009342731,0.0002002121,0.00004419966,0.0003232259,0.00004188121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007675721,"about_ca_system_score_gemma":0.0001906899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005299687,"about_ca_topic_score_gemma":0.000008324999,"domain_scores_codex":[0.9978648,0.000288541,0.0005960981,0.0001523683,0.0009389739,0.0001591497],"domain_scores_gemma":[0.9964147,0.0003193081,0.0001783101,0.0001689832,0.002845024,0.00007363468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001904282,0.000207725,0.001718212,0.00003863612,0.00002935064,0.00005502086,0.0001569608,0.003732504,0.9800201,0.004003422,0.0006367651,0.009210893],"study_design_scores_gemma":[0.007858197,0.008076749,0.2078176,0.002336313,0.0001621343,0.005066573,0.00132395,0.07293718,0.6558338,0.006390666,0.03140609,0.0007907595],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.835971,0.0001158879,0.13837,0.0007943193,0.0000304876,0.0004284129,0.000005853035,0.0000207517,0.02426331],"genre_scores_gemma":[0.9667906,0.000001687552,0.032313,0.0001260978,0.0004542722,0.000009453994,0.000006377607,0.00002456413,0.0002739896],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3241863,"threshold_uncertainty_score":0.246867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1604454488492129,"score_gpt":0.3854647556662347,"score_spread":0.2250193068170218,"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."}}