Introducing forensic entomology in cases of suspected animal neglect
Bibliographic record
Abstract
Cases of arthropod-infested, abandoned or abused animals are sometimes brought to the attention of veterinarians by animal welfare authorities, with the requirement for a full postmortem examination towards criminal or civil proceedings. In these situations, entomology is an important support tool for the pathologists' investigation since the presence of arthropod life cycle stages serve as reliable forensic markers, especially for blowflies which form the first waves of activity following death. In the present study, 70 cadavers from a total of 544 referred to the Institute of Veterinary Science, University of Liverpool, between 2009 and 2014 displayed evidence of infestation. Here, the authors introduce principles of applied entomology and simplified approaches for estimating the minimum time since death, relevant in the context of routine submissions and the broad remit of individual cases. Despite often limited availability of scene of the crime and local thermal data, the interpretation of the minimum postmortem interval has nonetheless proved valuable as an adjunct to the expert pathology report. However, future developments and enhanced accuracy in this area of animal welfare require resource and training in expertise, and agreed standardisation of both laboratory and field procedures.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".