The CISE-LOCEAN seawater isotopic database (1998–2021)
Bibliographic record
Abstract
Abstract. The characteristics of the CISE-LOCEAN seawater isotope dataset (δ18O, δ2H, referred to as δD) are presented (https://doi.org/10.17882/71186; Waterisotopes-CISE-LOCEAN, 2021). This dataset covers the time period from 1998 to 2021 and currently includes close to 8000 data entries, all with δ18O, three-quarters of them also with δD, associated with a date stamp, space stamp, and usually a salinity measurement. Until 2010, samples were analyzed by isotopic ratio mass spectrometry and since then mostly by cavity ring-down spectroscopy (CRDS). Instrumental uncertainty in this dataset is usually as low as 0.03 ‰ for δ18O and 0.15 ‰ for δD. An additional uncertainty is related to the isotopic composition of the in-house standards that are used to convert data to the Vienna Standard Mean Ocean Water (VSMOW) scale. Different comparisons suggest that since 2010 the latter have remained within at most 0.03 ‰ for δ18O and 0.20 ‰ for δD. Therefore, combining the two uncertainties suggests a standard deviation of at most 0.05 ‰ for δ18O and 0.25 ‰ for δD. For some samples, we find that there has been evaporation during collection and storage, requiring adjustment of the isotopic data produced by CRDS, based on d-excess (δD − 8×δ18O). This adjustment adds an uncertainty in the respective data of roughly 0.05 ‰ for δ18O and 0.10 ‰ for δD. This issue of conservation of samples is certainly a strong source of quality loss for parts of the database, and “small” effects may have remained undetected. The internal consistency of the database can be tested for subsets of the dataset when time series can be obtained (such as in the southern Indian Ocean or North Atlantic subpolar gyre). These comparisons suggest that the overall uncertainty of the spatially (for a cruise) or temporally (over a year) averaged data is less than 0.03 ‰ for δ18O and 0.15 ‰ for δD. However, 18 comparisons with duplicate seawater data analyzed in other laboratories or with other datasets in the intermediate and deep ocean suggest a larger scatter. When averaging the 18 comparisons done for δ18O, we find a difference of 0.082 ‰ with a standard error of 0.016 ‰. Such an average difference is expected due to the adjustments applied at LOCEAN to saline water data produced either by CRDS or isotope ratio mass spectrometry (IRMS), but the scatter found suggests that care is needed when merging datasets from different laboratories. Examples of time series in the surface North Atlantic subpolar gyre illustrate the temporal changes in water isotope composition that can be detected with a carefully validated dataset.
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How this classification was reachedexpand
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 | 0.004 | 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 | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".