{"id":"W3012400547","doi":"10.2196/18503","title":"The Role of the Global Health Development/Eastern Mediterranean Public Health Network and the Eastern Mediterranean Field Epidemiology Training Programs in Preparedness for COVID-19","year":2020,"lang":"en","type":"editorial","venue":"JMIR Public Health and Surveillance","topic":"Viral Infections and Outbreaks Research","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preparedness; Public health; Epidemiology; Mediterranean climate; Environmental health; Coronavirus disease 2019 (COVID-19); Pandemic; Field (mathematics); Training (meteorology); Geography; Medicine; Political science; Disease; Nursing; Meteorology; Infectious disease (medical specialty)","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":["metaresearch","metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.02059123,0.0004935337,0.001995955,0.0001133354,0.001370375,0.0001851116,0.0006378742,0.0005299403,0.00000623414],"category_scores_gemma":[0.01104812,0.0002658572,0.0002052717,0.0008795586,0.0007868261,0.0001076142,0.000378701,0.001484319,9.344986e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008535506,"about_ca_system_score_gemma":0.02128905,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003395928,"about_ca_topic_score_gemma":0.02219762,"domain_scores_codex":[0.989666,0.004168446,0.00211725,0.0009390854,0.0009150314,0.002194186],"domain_scores_gemma":[0.9892718,0.006158784,0.001331473,0.0006497864,0.0003303678,0.002257788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009351439,0.0000928829,0.09600624,0.00221066,0.0001350181,0.00000160208,0.01610745,0.000001390568,1.484417e-8,0.0003759757,0.2428298,0.6413038],"study_design_scores_gemma":[0.003717248,0.001179954,0.002562557,0.0002169691,0.000001939157,0.00003401268,0.003572957,0.003293177,6.542638e-9,0.000359244,0.9848666,0.0001954004],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.004654474,0.03827639,0.002174486,0.8112048,0.1293191,0.01350331,0.000365944,0.0001804949,0.0003210326],"genre_scores_gemma":[0.5400144,0.0134936,0.0006631766,0.08092541,0.3544171,0.006252144,0.003448261,0.0002340968,0.0005517937],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.7420368,"threshold_uncertainty_score":0.9999794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1590881018132662,"score_gpt":0.4233322241983649,"score_spread":0.2642441223850986,"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."}}