Permian metabolic bone disease revealed by microCT: Paget’s disease-like pathology in vertebrae of an early amniote
Bibliographic record
Abstract
Bone remodeling is an essential physiological process in growth and healing. In modern systems deviations from normal bone physiology in the form of pathologies aid in the understanding of normal bone metabolism. Here we use external morphology and X-ray microtomography to diagnose and describe a metabolic bone disease in an amniote from the early Permian. The specimen consists of two fused tail vertebrae of a small varanopid from early Permian (289 million years old) cave deposits near Richards Spur, Oklahoma, USA. Inspection of the outer morphology reveals that the fusion encompasses the vertebral centra, zygopophyses and haemal arches, with the fusion zones distinctly swollen on the left side of the specimen. With visualization of its internal structure by microCT, this specimen is diagnosed as a complex metabolic bone disease. The radiological imaging suggests a pathologically high bone turnover rate, as shown by abnormal bone formation in some areas and increased bone resorption in others. This supports that the varanopid suffered from a metabolic bone disease similar to Paget's disease of bone as seen in humans today, which is linked to both genetic and viral factors. This finding extends the occurrence of Paget-like disease to the early Permian, and-provided a viral component was present-would also be by far the oldest evidence of viral infection in the fossil record.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".