{"id":"W2911126099","doi":"10.1093/jhered/esz001","title":"The Expectations and Challenges of Wildlife Disease Research in the Era of Genomics: Forecasting with a Horizon Scan-like Exercise","year":2019,"lang":"en","type":"article","venue":"Journal of Heredity","topic":"Zoonotic diseases and public health","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Smithsonian Conservation Biology Institute; Colorado State University; Division of Environmental Biology; Morris Animal Foundation; National Science Foundation","keywords":"Wildlife; Genomics; Wildlife disease; Data science; Disease; Infectious disease (medical specialty); Biology; Environmental resource management; Ecology; Genome; Computer science; Medicine; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002103206,0.00006282461,0.0002444916,0.00008780559,0.00007292554,0.00001626243,0.0001389623,0.00002692052,0.00001222713],"category_scores_gemma":[0.0002406202,0.00003053545,0.00005446001,0.0001602825,0.0001497195,0.00009425706,0.00002584769,0.0003784995,4.841894e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004577945,"about_ca_system_score_gemma":0.0008900597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007649425,"about_ca_topic_score_gemma":0.00006200452,"domain_scores_codex":[0.9986241,0.0001885414,0.0003777413,0.00008460674,0.0005428693,0.000182161],"domain_scores_gemma":[0.9983185,0.0006568094,0.0002658775,0.0002205293,0.0003513111,0.0001869704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01569608,0.002968353,0.2026098,0.005887081,0.0004037034,0.0004401462,0.03709687,0.0002072484,0.0001116735,0.005897756,0.0061311,0.7225502],"study_design_scores_gemma":[0.006765926,0.006438481,0.766758,0.005027609,0.0002815063,0.0002657298,0.2016306,0.002459332,0.00002621708,0.003479613,0.006677296,0.0001897342],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769711,0.009690724,0.000005414857,0.01226109,0.0001016839,0.0003426392,0.000008294625,0.000001247164,0.0006177792],"genre_scores_gemma":[0.9963434,0.003217613,0.000161963,0.00004056907,0.000212012,0.000004841017,8.138396e-7,0.000007567954,0.00001126833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7223604,"threshold_uncertainty_score":0.1644413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08971216829806228,"score_gpt":0.3376871215076833,"score_spread":0.247974953209621,"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."}}