The effect of growth on stable nitrogen isotope ratios in subadult bone collagen
Bibliographic record
Abstract
Abstract Stable nitrogen isotopes have been used to reconstruct infant feeding practices as nursing infants have elevated δ 15 N ratios compared with their mothers. However, infancy is also a time of rapid growth, which may alter nitrogen isotope diet‐to‐tissue spacing. Several studies have documented a decrease in δ 15 N during growth in tissues with relatively fast accretion rates. This study investigates the effect that the growth of long bones, via collagen accretion, has on δ 15 N ratios. Long bones from individuals aged seven to nineteen years were obtained from a protohistoric ossuary in Ontario, Canada. Analysis of juveniles and adolescents permitted the examination of growth in a group who were not also nursing. It is concluded that a nitrogen isotope growth effect is not detectable in bone collagen from juveniles and adolescents, because: (1) δ 15 N ratios are not significantly different among the epiphyses, metaphyses and diaphysis of a growing long bone; (2) δ 15 N ratios are not significantly different between faster‐growing versus slower‐growing metaphyses; and (3) δ 15 N ratios are not significantly different between bones (or areas of a bone) that are still undergoing growth, versus bones that have ceased growing. The relatively slow speed of collagen accretion may explain why a growth effect is not manifested. Ultimately this research lends support to the use of nitrogen isotopes from bone collagen for infant feeding reconstructions. Copyright © 2009 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".