The subtleties of stress: A comparative analysis of skeletal lesions between the Medieval and post‐Medieval Black Friars cemetery population (13th to 17th centuries)
Bibliographic record
Abstract
Abstract The study of stress from an osteological perspective is challenging as we use skeletal remains to explore the lived experience and patterns of health. As an intricate overlap of multiple biological processes, the stress response system guides our understanding of how and why stress manifests as it does. Using traditional osteological methods of stress analysis, specifically cribra orbitalia, porotic hyperostosis, and enamel hypoplastic lesions, this study focuses on the relationship between these indicators to explore differences in stress manifestation in the Medieval and post‐Medieval periods in Denmark. Using the Black Friars cemetery population (13th–17th centuries), results show an increase in stress from the Medieval into the post‐Medieval period likely dictated by the strains of urbanism on a predominantly poor population. Additionally, a younger mean age at death was noted when multiple mild–moderate indicators were present as compared with one severe indicator being present. A recognition of the intricacies of the stress response effectively aids in the exploration of stress manifestation and the relationship, if any, between these well‐used skeletal indicators.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".