The use of wet chemical oxidation with high‐amplification isotope ratio mass spectrometry (WCO‐IRMS) to measure stable isotope values of dissolved organic carbon in seawater
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Bibliographic record
Abstract
Few measurements of the carbon stable isotope value (δ 13 C) of marine dissolved organic carbon (DOC), the largest pool of reduced carbon in the ocean, have been made because of analytical obstacles due to the interference of halides and the low amount of DOC in seawater. By using concentrated persulfate in a wet chemical oxidation organic carbon analyzer coupled to an isotope ratio mass spectrometry (WCO‐IRMS) the analytical obstacles are overcome. Key to this method is reducing the persulfate blank and increasing the IRMS signal with larger amplifier gain resistors. After these simple modifications, a 2 mL sample provides enough signal to make precise measurements of DOC concentration and δ 13 C value on up to 15 samples per day. Sodium persulfate (1.68 mol L −1 ) is cleaned by pre‐heating and sparging with ultrahigh purity helium. In the WCO analyzer, 6 mL cleaned persulfate is added to 2 mL sample at 98°C for 8.5 min to completely oxidize DOC to CO 2 . After quantitative measurement by nondispersive IR, the gases contained in the exhaust are swept through a cleanup reactor, separated by a GC column and introduced to the IRMS for δ 13 C measurement. Complete recovery of the DOC and δ 13 C values was confirmed with two DOC standards added individually to seawater. IRMS precision was confirmed by measuring a range of sea water samples. On several coastal water samples measured using this system, δ 13 C‐DOC values ranging from −22‰ to −25‰. These results were consistent with published reports of seawater δ 13 C‐DOC using other methods.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it