{"id":"W1979815956","doi":"10.3138/jvme.35.2.152","title":"Prevention and Preparedness: Working Together to Improve Public Health","year":2008,"lang":"en","type":"article","venue":"Journal of Veterinary Medical Education","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preparedness; Public health; Medicine; Medical education; Environmental health; Nursing; Political 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":[0.0451615,0.002675505,0.004071006,0.003007114,0.01456473,0.01841405,0.01099697,0.1171197,0.01759342],"category_scores_gemma":[0.114824,0.001783525,0.004510904,0.002761082,0.02361078,0.02738148,0.01636746,0.1365557,0.006194279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01510643,"about_ca_system_score_gemma":0.08003096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03986006,"about_ca_topic_score_gemma":0.06033495,"domain_scores_codex":[0.9522672,0.02318923,0.003697926,0.004293147,0.01074049,0.005812045],"domain_scores_gemma":[0.8563632,0.08068134,0.006134394,0.002494801,0.02662882,0.02769747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004001459,0.00005582189,0.0001637581,0.000399685,0.00005904592,0.0001289696,0.001246934,0.00007551304,0.00004863275,0.008920151,0.9772134,0.01164797],"study_design_scores_gemma":[0.000167989,0.0001005485,0.001483145,0.005172976,0.0001867486,0.0002522401,0.00793095,0.000311281,0.0002546205,0.0515025,0.9324363,0.0002007559],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0000328053,0.003183434,0.00007730474,0.978395,0.01772565,0.000005482309,0.000008080166,0.00000780311,0.0005644385],"genre_scores_gemma":[0.002486269,0.005519866,0.0005166477,0.9440683,0.04471788,0.00005329169,0.00001985733,0.00003869267,0.002579173],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1171197,"threshold_uncertainty_score":0.2388397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2478856412061253,"score_gpt":0.5323576508486548,"score_spread":0.2844720096425296,"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."}}