Data_Sheet_5_Assessing and improving on-farm biosecurity knowledge and practices among swine producers and veterinarians through online surveys and an educational website in Illinois, United States.PDF
Bibliographic record
Abstract
<p>There is a growing risk to the health and productivity of the Illinois and United States swine population from foreign and endemic infectious diseases. Effective on-farm biosecurity practices play a pivotal role in preventing these high-consequence pathogens from affecting swine farms. Veterinarians are essential in providing disease prevention advice to swine producers that can help them implement effective biosecurity practices on their farms. Our descriptive study objectives were to assess Illinois swine producers’ and veterinarians’ biosecurity perception, knowledge, and practices to identify knowledge gaps and address these by developing an online educational website. We developed two independent online questionnaires using Qualtrics<sup>XM</sup> software. Swine producer members of the Illinois Pork Producers Association and veterinarians registered with the Illinois State Veterinary Medical Association were contacted via e-mail through their associations and asked to complete an online survey. In total, 13 swine producers across 9 Illinois counties operating 82 farms (8 managed single farms and 5 managed multiple farms) responded to the swine producer survey. Despite some biosecurity awareness among swine producers, the need for a biosecurity-related outreach program was evident. Among the 7 swine veterinarian responders, 5 predominantly treated swine (oversaw an average of 21.6 farms), and 2 were mixed animal practitioners. The swine veterinarian survey showed a disconnect between their biosecurity perception and practices. We developed a biosecurity educational website and used Google Analytics to collect website traffic and user data. The 4 months of data showed good coverage that included the highest proportion of users from the Midwest and North Carolina, the largest swine-production regions in the US, and China and Canada, the leading producers of swine worldwide. The most accessed webpage was the resources page, and the swine diseases page had the highest engagement time. Our study highlights the effectiveness of combining online surveys with an educational website to assess and improve the biosecurity knowledge of swine producers and veterinarians that can be applied to assess and improve the biosecurity knowledge and practices of other livestock farmers.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".