Sulfur isotope analysis of collagen: Quality controls and proboscidean wetland habitats
Bibliographic record
Abstract
Sulfur isotopes ( δ 3 4 S values) have significant potential for addressing archaeological, paleontological, and paleoecological research questions. Studies of ancient materials rely on the assumption that δ 3 4 S values have been minimally altered by diagenesis , yet meaningful analyses of sulfur isotope preservation/alteration are rare. This paper has 3 objectives: (1) to review and revise previous approaches to evaluating sulfur isotope alteration of collagen, (2) to evaluate sulfur isotope preservation in Great Lakes mammoth ( Mammuthus spp.) and mastodon ( Mammut americanum ) bone, tooth, and tusk collagen, and (3) to make inferences about proboscidean diets and habitat preferences based on δ 34 S values. To evaluate sulfur isotope preservation in collagen we recommend 3 approaches. First, researchers should examine collagen %C, %N, and atomic C:N values, and exclude samples whose values fall outside the expected ranges (defined according to context-specific considerations). Second, researchers should examine collagen %S, C:S, and N:S values, and exclude samples that fall outside the ranges for modern taxa. These ranges are subject to revision, but this study provides a new compilation of modern mammalian collagen with %S = 0.14–0.63, C:S = 185–873, and N:S = 55–266 (n=119). Third, researchers should check for correlations between collagen δ 34 S and %S, C:S, or N:S values, which could suggest systematic alteration of sulfur isotope values due to sulfur contamination or amino acid loss. For our Great Lakes proboscideans, the first approach was insufficient to identify sulfur isotope alteration, but the second and third approaches led to the exclusion of 4 samples with probable alteration. Great Lakes proboscideans had lower δ 34 S values than recent taxa from the same region, and the δ 34 S of mastodons tended to be lower than those of mammoths. These results suggest that mammoths and (to a greater extent) mastodons consumed an abundance of plants rooted in anoxic freshwater wetland sediments.
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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 | 0.001 |
| 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 | 0.000 |
| 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".