Spatial variability in sulphur isotope values of archaeological and modern cod ( <i>Gadus morhua</i> )
Bibliographic record
Abstract
RATIONALE: This study presents the first sulphur isotope data of modern and archaeological cod (Gadus morhua) bone collagen, undertaken to identify large-scale spatial variability of significance as both baseline values for studies of human diet and a potential variable in isotope-based studies of fish trading. METHODS: Collagen was extracted from modern and archaeological cod bones using a weak HCl solution and analysed for its sulphur isotopic composition by isotope ratio mass spectrometry (IRMS). RESULTS: The archaeological cod have sulphur isotope values ranging from +9.1‰ to +18.2‰, whereas values for modern specimens range from +14.8‰ to +18.3‰. The modern data show values implying less freshwater influence, consistent with their offshore catch locations, but also corroborate some of the regional variability evident from the archaeological evidence. CONCLUSIONS: The archaeological data have a large range of sulphur isotope values compared with the modern populations, probably indicating they were taken from a wide range of geographic locations, including both coastal and offshore locales. They show broad trends of regional difference that may relate to both the fish populations targeted (e.g. 'inshore' versus 'offshore') and the baseline values of the local ecosystem (e.g. degree of freshwater input from river systems).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".