Ontogenetic profiles of dentine isotopes (δ15N and δ13C) reveal variable narwhal Monodon monoceros nursing duration
Bibliographic record
Abstract
Stable isotope analysis (SIA) of sequential dentine growth layer groups can be used to estimate the lifetime diet of individuals and infer major ontogenetic shifts such as the completion of nursing. We used SIA of dentine from narwhalMonodon monocerosembedded canine teeth to investigate ontogenetic dietary patterns, with a focus on nursing duration. We also determined whether nursing duration differed between sexes and between 2 periods during which narwhals may have undergone dietary shifts due to warming. Embedded teeth from both sexes were collected near Pond Inlet, Nunavut, Canada, in 1982 and 1983 (n = 17) and 2015 and 2017 (n = 14). Nursing duration ranged from ~2 to ~6 yr, with 60% of narwhals being nursed beyond the previously published estimate of <2 yr. The proportion of individuals nursed <2 yr versus >2 yr did not differ between sexes or periods. This study not only revealed that narwhals vary extensively in their nursing duration, but also indicated that extended nursing (>2 yr) with gradual introduction of solid food over this period was common. These findings provide insights into narwhal life-history strategies, as extended nursing may be another feature of a long-lived, slow-reproducing mammal adapted to unique polar conditions that are threatened by global warming.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".