{"id":"W4388882391","doi":"10.2196/40491","title":"Learning From COVID-19: What Would It Take to Be Better Prepared in the Eastern Mediterranean Region?","year":2023,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Viral Infections and Outbreaks Research","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"World Health Organization","keywords":"Public health; Preparedness; Business; Environmental health; Global health; Health policy; Public relations; Pandemic; Workforce; Health care; Economic growth; International health; Political science; Medicine; Coronavirus disease 2019 (COVID-19); Nursing; Economics; Disease","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008037004,0.0007466378,0.001240436,0.0009212081,0.004541509,0.006880408,0.002737066,0.008054083,0.0126534],"category_scores_gemma":[0.02244849,0.0003940783,0.001182541,0.0005422672,0.00411403,0.01102388,0.007190026,0.01074648,0.002875078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005832278,"about_ca_system_score_gemma":0.01865949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02540557,"about_ca_topic_score_gemma":0.04013951,"domain_scores_codex":[0.9951616,0.002369655,0.0001547054,0.000282566,0.0003256163,0.00170589],"domain_scores_gemma":[0.9891158,0.001391712,0.0006326045,0.0001558723,0.001435959,0.007268039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003402141,0.0008538195,0.03447823,0.004689384,0.0001963851,0.002224713,0.03370681,0.0003732516,0.0004593951,0.007963737,0.4836922,0.431022],"study_design_scores_gemma":[0.0003560288,0.001403335,0.08757578,0.02279639,0.0002946092,0.001788873,0.3414153,0.0008157987,0.0008253422,0.02635339,0.5158983,0.0004767514],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.03030288,0.02637487,0.0004914731,0.9294617,0.005282769,0.0001041717,0.0003855539,0.0001018332,0.007494715],"genre_scores_gemma":[0.4095225,0.09031609,0.006211552,0.4741625,0.006543525,0.0007766443,0.001243525,0.0001440651,0.01107951],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02540557,"threshold_uncertainty_score":0.05051541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1722307060080826,"score_gpt":0.4128848360110676,"score_spread":0.240654130002985,"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."}}