{"id":"W4291163699","doi":"10.1155/2022/8127055","title":"Design and Analysis of Hospital Throughput Maximization Algorithm under COVID-19 Pandemic","year":2022,"lang":"en","type":"article","venue":"Computational and Mathematical Methods in Medicine","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Throughput; Computer science; Maximization; Set (abstract data type); Coronavirus disease 2019 (COVID-19); Node (physics); Pandemic; Graph; Algorithm; Theoretical computer science; Mathematical optimization; Medicine; Mathematics; Engineering; Wireless","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005940069,0.0001694918,0.0009379832,0.0002888303,0.0001679936,0.000005058084,0.0001198872,0.00005737242,0.000365235],"category_scores_gemma":[0.0104248,0.0001233611,0.00006056598,0.0008743749,0.0004402419,0.00003592747,0.0002891685,0.000206008,2.638743e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001289188,"about_ca_system_score_gemma":0.00004606448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001986616,"about_ca_topic_score_gemma":8.698391e-7,"domain_scores_codex":[0.9970185,0.001321387,0.0007580856,0.0003544043,0.0003733839,0.0001742199],"domain_scores_gemma":[0.9670896,0.03233825,0.0002536538,0.000128459,0.00006706701,0.0001229846],"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":[0.0001054433,0.0008589639,0.01122978,0.0009257865,0.00157798,0.00002373417,0.01020871,0.2003972,0.00006928566,0.7165083,0.001129494,0.0569653],"study_design_scores_gemma":[0.0004312335,0.0001729513,0.002803486,0.0000143415,0.0003083205,0.000007583484,0.0005476953,0.3794055,6.988076e-7,0.6161706,0.00005524959,0.00008230205],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005256558,0.0005602875,0.9896268,0.003999385,0.0000502105,0.0003966422,0.00001035401,0.00004412802,0.0000556024],"genre_scores_gemma":[0.01582223,0.00009212772,0.982253,0.001668303,0.00002196879,0.00008907778,0.00001754966,0.00001052928,0.00002524006],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1790083,"threshold_uncertainty_score":0.9979108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4096161693691462,"score_gpt":0.5391621709962038,"score_spread":0.1295460016270576,"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."}}