Stable isotope analysis of dissolved organic carbon in Canada's eastern coastal waters
Bibliographic record
Abstract
Abstract The application of carbon stable isotope analysis of dissolved organic carbon (δ13C‐DOC) from natural seawater has been limited owing to the inherent difficulty of such analysis, with order of magnitude differences in interfering ions and analyte concentrations. High temperature catalytic oxidation allows for the attenuation of these interferences by precipitation of inorganic ions on quartz chips upstream from the oxidation catalyst. Using a chemical trap, the OI 1030C combustion DOC analyzer unit can be coupled to an IRMS, allowing for the analysis of low DOC content saline waters with relatively high throughput. The analytical limitations and large water volumes traditionally required for these types of analyses have prevented any large‐scale δ13C‐DOC studies. Here, we present δ13C‐DOC signatures for surface and bottom waters obtained along Canada's East Coast. Included in the study are samples from the Esquiman channel (between Newfoundland and Labrador), Lake Melville, the Saglek and Nachvak Fjords, the Hudson Strait and finally covering the salinity gradient across the St. Lawrence Estuary and Gulf. Measured δ13C‐DOC signatures ranged from predominantly marine values of −19.9 ± 0.3‰ (vs. VPDB) off the coast of Newfoundland to predominantly terrestrial signatures of −26.9 ± 0.1‰ in Lake Melville. We observed a large spread in δ13C‐DOC signatures for samples with a salinity of ≈ 35 between −19.9‰ and −23.3‰ demonstrating the difficulty associated to selecting a marine end‐member to be used in stable isotope mixing models to determine the fate of organic matter along the freshwater‐marine continuum.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| 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".