{"id":"W4312838448","doi":"10.1139/facets-2022-0064","title":"How not to manage a pandemic, and how to recover from it: Lessons from Ecuador","year":2022,"lang":"en","type":"article","venue":"FACETS","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pandemic; Outbreak; Coronavirus disease 2019 (COVID-19); Poverty; Economic growth; Development economics; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Public health; Inequality; Health care; Geography; Political science; Socioeconomics; Business; Economics; Medicine; Virology; Infectious disease (medical specialty); Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003777875,0.0002211568,0.0004721801,0.000283141,0.0001966981,0.0002661346,0.0004010905,0.00009307519,0.0009390021],"category_scores_gemma":[0.0005266282,0.0002810665,0.00008426907,0.0002922252,0.00001849823,0.0002333171,0.0006270874,0.0002812718,0.0004794191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003880825,"about_ca_system_score_gemma":0.00002544374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002303927,"about_ca_topic_score_gemma":0.0006277242,"domain_scores_codex":[0.9983994,0.00003496421,0.0002412324,0.0007924534,0.0000896634,0.0004422996],"domain_scores_gemma":[0.9987218,0.0002260136,0.0001683901,0.0005757262,0.00001280936,0.0002952051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005674651,0.0002929305,0.3483524,0.00006727008,0.0006586963,0.0001790021,0.02791737,0.001540511,0.008838974,0.003438134,0.5346488,0.0734984],"study_design_scores_gemma":[0.0008557438,0.00009975152,0.129693,0.00001324916,0.00001244675,0.000001860984,0.0006180025,0.0004217742,0.0002794386,0.004072416,0.863458,0.0004743219],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8945936,0.0004908941,0.002215313,0.09436493,0.0006483764,0.0004405629,0.00642049,0.00007028026,0.000755542],"genre_scores_gemma":[0.9730985,0.0000936636,0.0009468745,0.01742764,0.0001504584,0.00008027147,0.00007949503,0.00004372468,0.008079411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3288091,"threshold_uncertainty_score":0.9999743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08103166709112489,"score_gpt":0.279535847710936,"score_spread":0.1985041806198111,"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."}}