Guidelines for Accurate and Precise Stable Isotope Analysis of Calcite, Dolomite, and Magnesite Using a Carbonate Device for Continuous Flow‐Isotope Ratio Mass Spectrometry (CF‐IRMS)
Bibliographic record
Abstract
ABSTRACT Rationale Carbonate minerals are one of the most popular samples for an automated sample preparation system for CF‐IRMS, such as GasBench II and iso FLOW, but no standardized analytical protocols exist. This study gives guidelines on optimal analytic conditions for carbon and oxygen isotope analysis of Ca–Mg carbonates when using the carbonate–phosphoric acid reaction method. Methods Calcite (CaCO 3 –McMaster Carrara), dolomite (CaMg(CO 3 ) 2 –MRSI Dolomite), and magnesite (MgCO 3 –ROM Brazil Magnesite) with two grain size fractions (< 74 and 149–250 μm) were reacted with 103% (specific gravity of 1.92) phosphoric acid under He atmosphere in 12‐mL borosilicate glass vials to examine the full δ 13 C and δ 18 O evolution of acid‐liberated CO 2 for an extended reaction time of up to 12–30 days at 25°C and up to 3–7 days at 72°C. Results At 25°C, the optimal reaction time of calcite is 1 day for both grain size fractions while the optimal reaction time of 2–10 day is suggested for dolomite with a grain size of < 74 μm. At 72°C, 30‐min to 12‐h or 45‐min to 12‐h reaction is optimal for calcite with < 74‐μm or 149‐ to 250‐μm grain size fraction, respectively, whereas dolomite requires 12‐h to 1‐day reaction for both grain size fractions. The only optimal condition for magnesite is 6–7 days of reaction with < 74‐μm grain size at 72°C. Conclusions To determine precise and accurate δ 13 C and δ 18 O values of a carbonate mineral using the carbonate–phosphoric acid reaction method, an optimal reaction time must be assessed for a given analytical condition to avoid nonequilibrium isotope effects and unnecessary oxygen isotope exchange of acid‐liberated CO 2 in the carbonate reaction vessel. Our experimental result provides a guideline for the accurate and precise stable isotope analysis of Ca–Mg carbonate minerals.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.013 |
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".