{"id":"W3086476996","doi":"10.1007/s40273-020-00959-7","title":"On Pandemic Preparedness: How Well is the Modeling Community Prepared for COVID-19?","year":2020,"lang":"en","type":"article","venue":"PharmacoEconomics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Social distance; Public health; Pandemic; Preparedness; Socioeconomic status; Context (archaeology); Economic impact analysis; Social inequality; Social determinants of health; Psychological intervention; Epidemiology; Economic growth; Environmental health; Health economics; Development economics; Medicine; Inequality; Political science; Population; Geography; Coronavirus disease 2019 (COVID-19); Economics; Infectious disease (medical specialty); Nursing; Disease","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02935923,0.001250481,0.001746306,0.0015072,0.001588782,0.00608891,0.00362266,0.003172482,0.01106075],"category_scores_gemma":[0.2025083,0.0004840843,0.0009878413,0.001471289,0.00372588,0.01563983,0.003593563,0.006064884,0.0009737408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003476788,"about_ca_system_score_gemma":0.008419806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02047685,"about_ca_topic_score_gemma":0.01102062,"domain_scores_codex":[0.983752,0.0139284,0.0002563316,0.0006339503,0.0008203136,0.0006089691],"domain_scores_gemma":[0.844445,0.1297365,0.005992401,0.005724824,0.008985989,0.005115198],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005253733,0.000521514,0.02112885,0.0005377001,0.00058775,0.0001999097,0.001603816,0.1036647,0.0002466941,0.7010984,0.05634291,0.1135423],"study_design_scores_gemma":[0.00008588748,0.0001099163,0.002324631,0.0004244311,0.00007633193,0.00004117807,0.001936539,0.1129409,0.0002693537,0.8712063,0.01052753,0.00005702807],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.07928746,0.005684827,0.1842417,0.6854523,0.001952918,0.0001400936,0.0007860251,0.0004041062,0.04205062],"genre_scores_gemma":[0.914353,0.006095514,0.05820792,0.01366798,0.002938419,0.0002233953,0.0004481153,0.0002922711,0.003773458],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9706408,"threshold_uncertainty_score":0.1552683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5614062400663362,"score_gpt":0.4953550369935805,"score_spread":0.06605120307275575,"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."}}