Trends in Domestic Animal Medico‐Legal Pathology Cases Submitted to a Veterinary Diagnostic Laboratory 1998–2010*
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pathologists at veterinary diagnostic laboratories receive medico-legal cases from a variety of animal species for postmortem examination. A search of computerized records of the Animal Health Laboratory, University of Guelph, Guelph, Ontario, Canada from 1998 to 2010 identified 1706 medicolegal cases. These were categorized according to the history as criminal investigations, anesthetic-related deaths, insurance, litigation, malpractice cases, and regulatory cases. Statistically significant linear trends in the proportion of medicolegal cases for all animals and criminal cases for companion animals were identified over the 12 year period. Companion animals had significantly greater odds of being a medicolegal case in all categories except for insurance and regulatory cases, compared to noncompanion animals. Based on pathology reports for the 271 criminal cases, 43.1% were consistent with neglect, 29.2% were compatible with non-accidental injury, 4.80% were poisonings, 10.7% were deemed to be due to natural disease, and 11.43% were inconclusive.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it