{"id":"W2780181421","doi":"10.1016/j.prevetmed.2017.12.013","title":"Estimating the potential for disease spread in horses associated with an equestrian show in Ontario, Canada using an agent-based model","year":2017,"lang":"en","type":"article","venue":"Preventive Veterinary Medicine","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Outbreak; Demography; Psychological intervention; Attendance; Equine influenza; Medicine; Population; Disease control; Quarantine; Attack rate; Veterinary medicine; Geography; Environmental health; Virology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006065805,0.0001541733,0.0002382249,0.00001672275,0.0003472757,0.00003030031,0.000353867,0.00003530227,0.0000676081],"category_scores_gemma":[0.0002724526,0.00005816338,0.00003422821,0.00005437061,0.0001376906,0.00022858,0.00007306188,0.0001055065,9.984467e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002085629,"about_ca_system_score_gemma":0.0001302917,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8008713,"about_ca_topic_score_gemma":0.9794796,"domain_scores_codex":[0.9987553,0.0002505164,0.0002214678,0.0003162262,0.000148203,0.0003083047],"domain_scores_gemma":[0.9993916,0.0001209577,0.0001973017,0.0001156434,0.0000343245,0.0001402377],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006343813,0.001101394,0.8367746,0.00009158788,0.0001301739,0.001062959,0.0004737937,0.1204092,0.01662269,0.00015947,0.0003552978,0.01647499],"study_design_scores_gemma":[0.0004160015,0.0007723098,0.5673371,0.0001430321,0.00003731312,5.120802e-7,0.0001110565,0.430642,0.00000116818,0.000433499,0.00001492166,0.00009108057],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997526,0.00002463414,0.0005905504,0.001152772,0.00009229349,0.0005203864,0.00003970358,0.00001229821,0.00004131959],"genre_scores_gemma":[0.9989386,8.837038e-7,0.0003133999,0.0002634577,0.00009696336,0.00005180185,0.0002552566,0.000002047755,0.000077643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3102328,"threshold_uncertainty_score":0.2670999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1360236930633531,"score_gpt":0.3215707655675501,"score_spread":0.185547072504197,"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."}}