Bibliographic record
Abstract
Studies of living children demonstrate that early life stress impacts linear growth outcomes. Stresses affecting linear growth may also impact later life health outcomes, including increased cardiometabolic disease risk. Palaeopathologists also assess the growth of children recovered from bioarchaeological contexts. Early life stresses are inferred to affect linear growth outcomes, and measurements of skeletal linear dimensions alongside other bioarchaeological information may indicate the types of challenges faced by past groups. In clinical settings, the impacts of stress on growing children are typically measured by examining height. Palaeopathologists are limited to examining bone dimensions directly and must grapple with incomplete pictures of childhood experiences that may affect growth. Palaeopathologists may use clinical growth studies to inform observations among past children; however, there may be issues with this approach. Here, we review the relationship between contemporary and palaeopathological studies of child and adolescent growth. We identify approaches to help bridge the gap between palaeopathological and biomedical growth studies. We advocate for: the creation of bone-specific growth reference information using medical imaging and greater examination of limb proportions; the inclusion of children from different global regions and life circumstances in contemporary bone growth studies; and greater collaboration and dialogue between palaeopathologists and clinicians as new studies are designed to assess linear growth past and present. We advocate for building stronger bridges between these fields to improve interpretations of growth patterns across human history and to potentially improve interventions for children living and growing today.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.150 | 0.046 |
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".