{"id":"W3092052550","doi":"10.1093/eurpub/ckaa165.493","title":"Brain drain of Tunisian competencies: The case of health professionals","year":2020,"lang":"en","type":"article","venue":"European Journal of Public Health","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workforce; Globalization; Pace; Brain drain; Population; Public health; Business; Economic growth; Political science; Medicine; Nursing; Geography; Environmental health; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.006492264,0.0006133164,0.000424102,0.001545951,0.02496925,0.007878272,0.00161537,0.003417297,0.007911467],"category_scores_gemma":[0.00731453,0.0003670548,0.0003770606,0.001526501,0.01202135,0.004270657,0.01137174,0.004211906,0.0004831016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01649691,"about_ca_system_score_gemma":0.02131431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06620642,"about_ca_topic_score_gemma":0.08812046,"domain_scores_codex":[0.9917656,0.004436312,0.0001729763,0.0002769782,0.0005283338,0.002819878],"domain_scores_gemma":[0.9924184,0.003004301,0.0008740125,0.0001922855,0.0009477838,0.002563259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00004348718,0.000109825,0.01343161,0.0002238696,0.00001326238,0.007192012,0.948392,0.0001017101,0.0004629882,0.01388179,0.005355719,0.01079173],"study_design_scores_gemma":[0.000004701056,0.00003071546,0.003444719,0.0003159459,0.000004852449,0.0008004485,0.9731472,0.0000855469,0.000142061,0.0009830898,0.0210294,0.00001129227],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9318215,0.001983047,0.0005287809,0.04504897,0.0002303554,0.00006532217,0.00005280162,0.000009153991,0.02025993],"genre_scores_gemma":[0.9909298,0.000707245,0.0002287776,0.003898501,0.0000541938,0.00002968185,0.00001297238,0.000007731433,0.004131036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06620642,"threshold_uncertainty_score":0.1316421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1898339804057446,"score_gpt":0.4524923954059002,"score_spread":0.2626584150001556,"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."}}