{"id":"W4223634248","doi":"10.2196/28965","title":"Current and Future Needs for Human Resources for Ethiopia’s National Health Information System: Survey and Forecasting Study","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"HRHIS; Human resources; Workforce; Health human resources; Business; Delphi method; Information system; Health policy; Public health informatics; Environmental health; Medicine; Public health; Political science; Nursing; Computer science","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":[0.002788363,0.0002072802,0.0001668021,0.001847657,0.0008327509,0.001398461,0.0004468358,0.0005956219,0.002578449],"category_scores_gemma":[0.004409592,0.0002469066,0.0003760169,0.002923924,0.0002370709,0.001758907,0.0005733753,0.0006523236,0.0003673592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002747967,"about_ca_system_score_gemma":0.003197482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01943916,"about_ca_topic_score_gemma":0.01901455,"domain_scores_codex":[0.9990255,0.0003011805,0.000154023,0.00008339816,0.0001632527,0.0002726937],"domain_scores_gemma":[0.9963169,0.001433618,0.0008637031,0.00008965401,0.0007248856,0.0005712021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003061132,0.0001805495,0.9730522,0.0001939638,0.00002321174,0.0002585951,0.005023965,0.0008930449,0.0001855898,0.0005877555,0.002632518,0.01693796],"study_design_scores_gemma":[0.000006735148,0.0001770058,0.9365649,0.0002623752,0.00002361494,0.0003895199,0.04984191,0.004896674,0.0002076802,0.0002433298,0.007357756,0.00002846408],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992793,0.000309222,0.0004638981,0.00127246,0.00001295334,0.00007376113,0.002536324,0.000009999282,0.002528589],"genre_scores_gemma":[0.9970612,0.0005224545,0.0008780884,0.0001612577,0.000009907968,0.00009802961,0.0008469592,0.000001751339,0.0004204478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01943916,"threshold_uncertainty_score":0.038652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03907756488716146,"score_gpt":0.3858697379897628,"score_spread":0.3467921731026013,"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."}}