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
Bibliographic record
Abstract
Few measurements of the carbon stable isotope value (δ13C) 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 δ13C 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 CO2. 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 δ13C measurement. Complete recovery of the DOC and δ13C 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, δ13C‐DOC values ranging from −22‰ to −25‰. These results were consistent with published reports of seawater δ13C‐DOC using other methods.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".