Suitability of selected free‐gas and dissolved‐gas sampling containers for carbon isotopic analysis
Bibliographic record
Abstract
RATIONALE: Storage trials were conducted for 2 to 3 months using a hydrocarbon and carbon dioxide gas mixture with known carbon isotopic composition to simulate typical hold times for gas samples prior to isotopic analysis. A range of containers (both pierced and unpierced) was periodically sampled to test for δ(13)C isotopic fractionation. METHODS: Seventeen containers were tested for free-gas storage (20°C, 1 atm pressure) and 7 containers were tested for dissolved-gas storage, the latter prepared by bubbling free gas through tap water until saturated (20°C, 1 atm) and then preserved to avoid biological activity by acidifying to pH 2 with phosphoric acid and stored in the dark at 5°C. Samples were extracted using valves or by piercing septa, and then introduced into an isotope ratio mass spectrometer for compound-specific δ(13)C measurements. RESULTS: For free gas, stainless steel canisters and crimp-top glass serum bottles with butyl septa were most effective at preventing isotopic fractionation (pierced and unpierced), whereas silicone and PTFE-butyl septa allowed significant isotopic fractionation. FlexFoil and Tedlar bags were found to be effective only for storage of up to 1 month. For dissolved gas, crimp-top glass serum bottles with butyl septa were again effective, whereas silicone and PTFE-butyl were not. FlexFoil bags were reliable for up to 2 months. CONCLUSIONS: Our results suggest a range of preferred containers as well as several that did not perform very well for isotopic analysis. Overall, the results help establish better QA/QC procedures to avoid isotopic fractionation when storing environmental gas samples. Recommended containers for air transportation include steel canisters and glass serum bottles with butyl septa (pierced and unpierced).
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".