A Survey of Attitudes of Board-Certified Veterinary Pathologists to Forensic Veterinary Pathology
Bibliographic record
Abstract
An electronic survey was conducted to determine the attitudes of veterinary pathologists toward forensic pathology and the adequacy of their training in the discipline. The survey was sent to 1933 diplomates of the American College of Veterinary Pathologists and 311 completed responses were analyzed. Of respondents, 80% report receiving at least 1 type of medicolegal case, with cases from law enforcement received most frequently. Most (74%) of the respondents indicated that their previous training did not prepare them adequately to handle forensic cases and almost half of the respondents (48%) indicated that they needed more training on serving as an expert witness. Relative risk ratios (RRR) and odds ratios (OR) were generated to determine the strength of a statistically significant association. Responses from a free-text entry question determining additional training needs could be grouped into 3 main categories: (1) veterinary forensic pathology science and procedures, (2) documentation, evidence collection and handling, and (3) knowledge of the medicolegal system. Last, a field for additional comments or suggestions regarding veterinary forensic pathology was completed by 107 respondents and many reinforced the need for training in the categories previously described. The survey highlights that a significant proportion of diplomates of the American College of Veterinary Pathologists are currently engaged in veterinary forensic pathology but feel their training has not adequately prepared them for these cases. Hopefully, the survey results will inform the college and residency training coordinators as they address the training requirements for an important emerging discipline.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".