{"id":"W1961864985","doi":"10.5210/ojphi.v7i1.5698","title":"Keeping Public Health Surveillance Practice up to Speed: a Training Strategy to Build Capacity","year":2015,"lang":"en","type":"article","venue":"Online Journal of Public Health Informatics","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada","funders":"Public Health Agency; Public Health Agency of Canada","keywords":"Public health; Public relations; Function (biology); Public health surveillance; Globalization; Medicine; Knowledge management; Training (meteorology); Business; Computer science; Data science; Political science; Nursing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03446788,0.001065482,0.0005787839,0.003020988,0.009286175,0.01331151,0.007170999,0.007947613,0.02172283],"category_scores_gemma":[0.056337,0.001154503,0.001149441,0.001525751,0.005764235,0.02118426,0.03294929,0.01099944,0.007055512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01078601,"about_ca_system_score_gemma":0.07889996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004197021,"about_ca_topic_score_gemma":0.006056098,"domain_scores_codex":[0.9793317,0.01083434,0.0006262762,0.001780793,0.003126262,0.004300748],"domain_scores_gemma":[0.9149044,0.01878977,0.003899967,0.006148747,0.01091479,0.04534234],"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":[0.0002782703,0.007424331,0.01523427,0.001517418,0.00006820666,0.001037574,0.07530985,0.003143588,0.003808831,0.0937618,0.2726197,0.5257962],"study_design_scores_gemma":[0.0006370574,0.001954835,0.02242628,0.004536573,0.00008097461,0.001172139,0.09172099,0.009580621,0.004978772,0.1089619,0.7536588,0.0002911325],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.1609074,0.001620785,0.09123634,0.5819274,0.004812058,0.007512573,0.0003070841,0.003261743,0.1484146],"genre_scores_gemma":[0.6410673,0.001670039,0.2412493,0.05286858,0.001192676,0.007922958,0.0005102323,0.0005213208,0.05299753],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03446788,"threshold_uncertainty_score":0.1822858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5084913057227917,"score_gpt":0.5403937782196475,"score_spread":0.03190247249685585,"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."}}