Multi-level spondylolysis at Egiin Gol: A case from Xiongnu period Mongolia
Bibliographic record
Abstract
OBJECTIVE: This paper presents and discusses the aetiology of an extreme case of multi-level spondylolysis with unique presentation. MATERIALS: The affected individual is an adult male from Xiongnu period (209 BCE to 93 CE) Egiin Gol, northern Mongolia. METHODS: Analyses were limited to macroscopic and non-invasive methods. RESULTS: Seven complete spondylolytic clefts were documented on four vertebrae between T12 and L4, with only one located on L4, where most cases of spondylolysis occur, and four defects had atypical morphology. Evidence of spondylolisthesis was also observed. CONCLUSIONS: Congenital susceptibility to spondylolysis, combined with a physically demanding lifestyle, likely account for the condition's unusual manifestation. SIGNIFICANCE: The significance of this case its severity (one of the most extreme documented from archaeological contexts) and unusual presentation (location of the clefts and their atypical morphology). LIMITATIONS: Only a small sample (< 30) of Xiongnu period human remains were available for comparison. SUGGESTIONS FOR FURTHER RESEARCH: Interpretations from this case study would benefit from a more extensive analysis of spondylolysis, biomechanical stress, and acute trauma on the nomadic pastoral populations of northern Mongolia, including those pre-dating and post-dating the Xiongnu.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".