Pitfalls in comparing modern hair and fossil bone collagen C and N isotopic data to reconstruct ancient diets: a case study with cave bears (<i>Ursus spelaeus</i>)
Bibliographic record
Abstract
Stable isotope analyses provide one of the few means to evaluate diet of extinct taxa. However, interpreting isotope data from bone collagen of extinct animals based on isotopic patterns in different tissues of modern animal proxies is precarious. For example, three corrections are needed before making comparisons of recent hair and ancient bone collagen: calibration of carbon-13 variations in atmospheric CO2, different isotopic discrimination between diet-hair keratin and diet-bone collagen, and time averaging of bone collagen versus short-term record in hair keratin. Recently, Robu et al. [Isotopic evidence for dietary flexibility among European Late Pleistocene cave bears (Ursus spelaeus). Can J Zool. 2013;91:227-234] published an article comparing extant carbon (δ(13)C) and nitrogen (δ(15)N) stable isotopic data of European cave bear bone collagen with those of Yellowstone Park grizzly bear hair in order to test the prevailing assumption of a largely vegetarian diet among cave bears. The authors concluded that cave bears were carnivores. This work is unfortunately unfounded as the authors failed to consider the necessary corrections listed above. When these corrections are applied to the Romanian cave bears, these individuals can be then interpreted without involving consumption of high trophic-level food, and environmental changes are probably the reason for the unusual isotopic composition of these cave bears in comparison with other European cave bears, rather than a change of diet. We caution researchers to pay careful attention to these factors when interpreting feeding ecology of extinct fauna using stable isotope techniques.
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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 | 0.040 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".