{"id":"W4406344411","doi":"10.1136/bmjgh-2024-016313","title":"Wildlife policy, the food system and One Health: a complex systems analysis of unintended consequences for the prevention of emerging zoonoses in China, the Democratic Republic of the Congo and the Philippines","year":2025,"lang":"en","type":"article","venue":"BMJ Global Health","topic":"Zoonotic diseases and public health","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre for Global Health Research; York University","funders":"Canadian Institutes of Health Research; York University; Society for Conservation Biology; Cedar Tree Foundation","keywords":"China; Unintended consequences; Wildlife; Democracy; People's Republic; Political science; Economic growth; Public health; Pandemic; Coronavirus disease 2019 (COVID-19); Development economics; Environmental health; Geography; Environmental protection; Medicine; Politics; Biology; Disease; Ecology; Economics","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":[0.01072172,0.0005249708,0.0003820203,0.004755883,0.002169666,0.004434504,0.000939677,0.001321033,0.003320013],"category_scores_gemma":[0.0192721,0.0003408478,0.0008203029,0.003815503,0.003292171,0.004648851,0.00263127,0.001178086,0.00006429446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02087037,"about_ca_system_score_gemma":0.01366816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07322174,"about_ca_topic_score_gemma":0.0614157,"domain_scores_codex":[0.9954137,0.003351853,0.0001667745,0.0002775928,0.0002813441,0.0005087443],"domain_scores_gemma":[0.9769145,0.01799531,0.002566299,0.000429857,0.00139389,0.00070023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002785427,0.0004568983,0.5102257,0.00308908,0.0009678174,0.004125723,0.07265089,0.08346884,0.0009554694,0.2339547,0.003939236,0.08588714],"study_design_scores_gemma":[0.00009014219,0.0008106056,0.4093762,0.004568276,0.001219498,0.0005067731,0.2159044,0.1855271,0.001448417,0.1480106,0.03235135,0.0001866887],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9521843,0.004253272,0.01439868,0.0110346,0.00005349909,0.0005541023,0.0008251684,0.00005079642,0.01664567],"genre_scores_gemma":[0.9966958,0.0007250219,0.002024953,0.0001010251,0.000004871333,0.0001188547,0.00007425527,0.00000383869,0.0002514168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07322174,"threshold_uncertainty_score":0.1514258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04596191151028686,"score_gpt":0.3943350140118759,"score_spread":0.348373102501589,"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."}}