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Farm-Level Biosecurity and Antimicrobial Use in Pig Production: An Integrated Inferential and Explainable Machine Learning Analysis.

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پخش حرفه‌ای فارسی و انگلیسی

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خواندن هوشمند فارسی و انگلیسی در حال آماده‌سازی صداهای مرورگر…
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چکیده اصلی

Internal biosecurity may be associated with antimicrobial use (AMU) in pig production, but observational associations, predictions and explanations of fitted models answer different questions. We analysed 1110 farm-month-age-group units from 18 Hungarian pig farms; an original post hoc restriction retained 939 units from 13 farms. The continuous endpoint was the natural logarithm of one plus a defined AMU index formed by summing substance-specific active ingredient mass-to-recorded-weight ratios. The study-specific biosecurity instrument was used for within-farm monitoring and was not externally validated. We retained a 2 × 2 matrix of unfiltered/filtered and composite/separate-variable models, with categorical animal-group separation, age-group adjustment and farm-cluster uncertainty. In the unfiltered separate-variable model, recorded separation code 2 versus code 0 was associated with a higher log AMU index (β = 0.205; CR1-t 95% CI 0.013-0.397; p = 0.037), although the wild-cluster p-value was 0.116 and sensitivity estimates varied with adjustment. Code 3 binary contrasts were too sparse for precise effect quantification. Four ML families were evaluated using nested farm-grouped and leave-one-farm-out validation. For the inner-selected biosecurity-plus-age procedure, the unfiltered pooled R2 was -0.101 and -0.187, respectively. SHAP retained an exploratory role in explaining held-out tree model predictions. The results identify model-dependent observational patterns but do not establish a causal biosecurity effect or reliable prediction for new farms.

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کلیدواژه‌ها

SHAPantimicrobial usebiosecurity practiceexplainable machine learningswine farmingveterinary public health
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