Using microscopy to improve a diagnosis: an isolated case of tuberculosis‐induced hypertrophic osteopathy in archaeological dog remains
Bibliographic record
Abstract
Abstract The use of histology to estimate age, understand taphonomic history and diagnose disease in human skeletal and mummified remains is a well‐known method. Even though non‐human animals experience stress and disease similar to humans, microscopy is rarely applied to faunal remains to obtain a diagnosis. Histological results from a 16th‐century Iroquoian dog which had previously been diagnosed by macroscopic and molecular methods with tuberculosis‐induced hypertrophic osteopathy (HPO) are presented here. Comparisons indicate that canid microscopic skeletal manifestations of HPO are reminiscent of human alterations caused by this condition. In addition, the microscopy reveals an aggressive form of HPO that was chronic in nature which could not be identified by either macroscopic or molecular methods. By providing an extension to the original diagnosis, the impact of a chronic case of tuberculosis is discussed. This study helps to emphasise the utility of palaeohistopathology in both biological anthropology and zooarchaeology, as it allows for a deeper discussion of the manifestation of HPO and the impact of tuberculosis on both dogs and humans. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".