A sealed‐tube method for offline δ <sup>13</sup> C analysis of CO <sub>2</sub> via a Gas Bench II continuous‐flow isotope ratio mass spectrometer
Bibliographic record
Abstract
Rationale The isotopic measurement of environmental sample CO 2 via isotope ratio mass spectrometry (IRMS) can present many analytical challenges. In many offline applications, exceedingly few samples can be prepared per day. In such applications, long‐term storage (months) of sample CO 2 is desirable, in order to accumulate enough samples to warrant a day of isotopic measurements. Conversely, traditional sample tube cracker systems for dual‐inlet IRMS offer a capacity for only 6–8 tubes and thus limit throughput. Here we present a simple method to alleviate these concerns using a Gas Bench II gas handling device coupled with continuous‐flow IRMS. Methods Sample preparation entails the cryogenic purification and quantification of CO 2 on a vacuum line. Sample CO 2 splits are expanded from a known volume to several sample ports and allowed to isotopically equilibrate (homogenize). Equilibrated CO 2 splits are frozen into 3 mm outer diameter Pyrex break‐seals and sealed under vacuum with a torch to a length of 5.5 cm. Sample break‐seals are scored, placed into 12 mL Labco Exetainer ® vials, purged with ultrahigh‐purity helium, cracked inside the capped helium‐flushed vials and subsequently measured via a Gas Bench equipped IRMS instrument using a CTC Analytics PAL autosampler. Results Our δ 13 C results from NIST and internal isotopic standards, measured over a time period of several years, indicate that the sealed‐tube method produces accurate δ 13 C values to a precision of ±0.1‰ for samples containing 10–35 μgC. The tube cracking technique within Exetainer vials has been optimized over a period of 10 years, resulting in decreased sample failure rates from 5–10% to <1%. Conclusions This technique offers an alternative method for δ 13 C analyses of CO 2 where offline isolation and long‐term storage are desired. The method features a much higher sample throughput than traditional dual‐inlet IRMS cracker setups at similar precision (±0.1‰).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".