{"id":"W3036565706","doi":"10.46784/e-avm.v9i1.96","title":"COMPARATIVE ANALYSIS OF DIFFERENT STRATEGIES FOR THE CONTROL OF CLASSICAL SWINE FEVER IN THE REPUBLIC OF SERBIA USING MONTE CARLO SIMULATION","year":2016,"lang":"en","type":"article","venue":"Archives of Veterinary Medicine","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Biological Sciences","funders":"","keywords":"Classical swine fever; Biosecurity; Vaccination; Disease Eradication; Disease control; Monte Carlo method; Environmental health; Veterinary medicine; Medicine; Disease; Virology; Statistics; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003373466,0.0008263824,0.001352605,0.001386838,0.0005466679,0.0009908524,0.000956119,0.001211929,0.00146701],"category_scores_gemma":[0.007229437,0.0005189429,0.001200884,0.0006138933,0.0005297973,0.0006785694,0.0005242602,0.0006972067,0.00009812579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002215563,"about_ca_system_score_gemma":0.002207003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03401033,"about_ca_topic_score_gemma":0.01460642,"domain_scores_codex":[0.998637,0.0008577528,0.00004745753,0.0001028327,0.0001034968,0.0002514855],"domain_scores_gemma":[0.9916736,0.006705984,0.0005570846,0.0001745739,0.0006060328,0.000282839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001940812,0.000104212,0.002560806,0.00006133219,0.00007710304,0.00003764794,0.00001909982,0.9929513,0.0002784899,0.0009044178,0.0001093937,0.002702142],"study_design_scores_gemma":[0.00007629838,0.0005501874,0.002619484,0.00003106876,0.0001040876,0.00001898916,0.00007176981,0.9953275,0.000372156,0.0006020488,0.0002096956,0.0000167935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9649795,0.001436534,0.02551441,0.0003098825,0.00006024398,0.0002468456,0.0002628322,0.0001199784,0.007069769],"genre_scores_gemma":[0.9957288,0.0002632322,0.003392293,0.00003170785,0.000003941959,0.0001077829,0.0001007325,0.000007883757,0.0003636478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03401033,"threshold_uncertainty_score":0.06762469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1539746311072493,"score_gpt":0.3590723477098429,"score_spread":0.2050977166025935,"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."}}