{"id":"W3161021559","doi":"10.1038/s41591-021-01381-y","title":"Health systems resilience in managing the COVID-19 pandemic: lessons from 28 countries","year":2021,"lang":"en","type":"review","venue":"Nature Medicine","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":1253,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Resilience (materials science); Public health; Pandemic; Government (linguistics); Coronavirus disease 2019 (COVID-19); Workforce; Psychological resilience; Public relations; Corporate governance; Service delivery framework; Political science; Economic growth; Business; Medicine; Service (business); Disease; Psychology; Nursing; Infectious disease (medical specialty); Economics; Marketing","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":[],"consensus_categories":[],"category_scores_codex":[0.005063768,0.0009354692,0.001823621,0.00234763,0.000424061,0.002281603,0.0011907,0.001934964,0.004928905],"category_scores_gemma":[0.01070943,0.0003081911,0.001197746,0.00327485,0.001848104,0.002967251,0.002539256,0.003068518,0.0005522096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002660234,"about_ca_system_score_gemma":0.008409724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007328236,"about_ca_topic_score_gemma":0.01025597,"domain_scores_codex":[0.9991393,0.00047262,0.00009378992,0.00007449256,0.0001295642,0.00009020282],"domain_scores_gemma":[0.9930184,0.005689463,0.0004401341,0.0001433723,0.0004607382,0.0002477996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001104134,0.00006308157,0.0007030503,0.03263097,0.0005981587,0.0001392126,0.0003898425,0.002299424,0.00009177248,0.06317988,0.02659347,0.8732007],"study_design_scores_gemma":[0.0001153707,0.0001930061,0.004311211,0.118677,0.0009220915,0.0005881638,0.001458193,0.0006757214,0.0002333986,0.09191618,0.7808213,0.00008834524],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001522781,0.9948755,0.0002111052,0.003824566,0.0001592566,0.000004361313,0.00002405643,0.00000495366,0.0007439172],"genre_scores_gemma":[0.003819252,0.9948711,0.0003047965,0.0006776638,0.00019967,0.00001403569,0.00001870594,0.00000227193,0.00009248584],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007328236,"threshold_uncertainty_score":0.02678013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3946018944234865,"score_gpt":0.5552419931599158,"score_spread":0.1606400987364294,"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."}}