{"id":"W2061454984","doi":"10.1016/j.prevetmed.2004.11.010","title":"Monte Carlo simulation of animal-product violations incurred by air passengers at an international airport in Taiwan","year":2005,"lang":"en","type":"article","venue":"Preventive Veterinary Medicine","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Food Inspection Agency","funders":"Centers for Disease Control and Prevention; National Taiwan University","keywords":"Monte Carlo method; Nationality; International airport; Product (mathematics); Quarantine; Business; Statistics; Transport engineering; Engineering; Geography; Mathematics; Medicine; Immigration","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":[0.000960211,0.0007013585,0.001018677,0.0008505576,0.0008956002,0.0009962204,0.00144323,0.002474657,0.002822701],"category_scores_gemma":[0.004098862,0.0008269555,0.001023912,0.0008705449,0.0009506122,0.0007413222,0.00079933,0.001521944,0.0002047389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001958204,"about_ca_system_score_gemma":0.002089737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1542616,"about_ca_topic_score_gemma":0.0771458,"domain_scores_codex":[0.9995297,0.000152098,0.00002595624,0.00007503735,0.00004888686,0.0001683109],"domain_scores_gemma":[0.995486,0.002858848,0.000541012,0.0001700489,0.0004534718,0.0004906827],"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":[0.0001423423,0.0001040196,0.0106241,0.000007665188,0.0000397132,0.0001696411,0.00003043247,0.9876952,0.0001349785,0.0004209094,0.0001671043,0.0004638903],"study_design_scores_gemma":[0.00002136983,0.00005513677,0.002538852,0.000002321225,0.0000177981,0.00001754834,0.00008013345,0.9970023,0.00007360447,0.0001407287,0.0000406837,0.000009454358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962226,0.00004501813,0.002156533,0.0001427439,0.00001676332,0.00002224056,0.0002473213,0.00004281276,0.001104009],"genre_scores_gemma":[0.9985089,0.00002059217,0.0007079552,0.00001821648,0.000003697558,0.0000140055,0.0002215164,0.000006940899,0.0004981243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1542616,"threshold_uncertainty_score":0.3067275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05938447756711842,"score_gpt":0.3333380334949445,"score_spread":0.2739535559278261,"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."}}