A new online technique for the simultaneous measurement of the <i>δ</i> <sup>13</sup> C value of dissolved inorganic carbon and the <i>δ</i> <sup>18</sup> O value of water from a single solution sample using continuous‐flow isotope ratio mass spectrometry
Bibliographic record
Abstract
RATIONALE: The oxygen isotope study of water reservoirs (δ(18)OH2O values) and the carbon isotope study of dissolved inorganic carbon (δ(13)CDIC values) are powerful tools to decipher Earth's past and present environmental changes. This study presents a novel online analytical technique, namely the DIC evolved CO2 Gas Equilibration Method (DIC-CO2-GEM), in which the δ(18)OH2O and δ(13)CDIC values can be simultaneously determined from a single solution sample. METHODS: The DIC-CO2-GEM measures both δ(18)OH2O and δ(13)CDIC values concurrently by combining the fundamental principles of the classic CO2-H2O equilibration and gas evolution methods, respectively. Phosphoric acid is used to convert dissolved inorganic carbon in a solution sample of 0.2 mL into gaseous CO2, which is then equilibrated with the solution at 25 °C. The oxygen and carbon isotope compositions are subsequently determined via continuous-flow isotope ratio mass spectrometry from the single solution sample. RESULTS: Results obtained employing the DIC-CO2-GEM are in good agreement (<± 0.07‰ for δ(18)OH2O values and < < ± 0.1‰ for δ(13)CDIC values) with those acquired using each of the traditional techniques. For both oxygen and carbon isotope measurements, an addition of 0.01 mL phosphoric acid yields the most consistent results between our technique and the traditional methods. CONCLUSIONS: Devised to combine the traditional approaches independently assessing δ(18)OH2O and δ(13)CDIC values, the DIC-CO2-GEM is less complex and highly efficient. It preserves the modern precision requirements for oxygen (± 0.09‰) and carbon (± 0.18‰) isotope analyses while accurately measuring both parameters simultaneously. This innovative method generates an abundance of data while minimizing resources and is suitable for a variety of practical applications.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".