Forensic evaluation of a dog with an embedded chain collar and corresponding wound age estimation
Bibliographic record
Abstract
The body of a young intact male dog was presented with an embedded chain collar around his neck as possible evidence in proceedings under the Criminal Code of Canada. A photographic record was made for court purposes. The circumference of the collar versus the adjacent unaffected neck was measured, showing the collar to be 15% shorter than was necessary to be compatible with non-injury to the dog while alive. Granulation tissue and fibrosis were grossly and histologically evaluated to help estimate the age of the wound. The granulation tissue at its deepest point was 2.0 cm. Considering granulation tissue begins formation 3–5 days post-injury and forms at a rate of 0.4–1.0 mm per day, the initial age of the wound was estimated at 23–55 days; however, given the re-epithelialization and fibrous strength of the affected tissue as well as the presence of haired skin around the links, the time estimate was determined to be more likely in the order of 4–6 months. Findings were later used in court as evidence in the charge of unnecessary pain, suffering and injury to an animal under Section 445.1(1)(a) of the Criminal Code. Testimony at the trial supported the estimated age of the wound. The owner was found guilty, fined Can$1000, placed on probation for two years, and prohibited for life from owning animals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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 source (direct Gemma or distilled Codex), 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".