An improved, automated whole air sampler and gas chromatography mass spectrometry analysis system for volatile organic compounds in the atmosphere
Bibliographic record
Abstract
Abstract. Volatile organic compounds were quantified during two aircraft-based field campaigns using highly automated, whole air samplers with expedited post-flight analysis via a new custom-built, field-deployable gas chromatography–mass spectrometry instrument. During flight, air samples were pressurized with a stainless steel bellows compressor into electropolished stainless steel canisters. The air samples were analyzed using a novel gas chromatograph system designed specifically for field use which eliminates the need for liquid nitrogen. Instead, a Stirling cooler is used for cryogenic sample pre-concentration at temperatures as low as −165 °C. The analysis system was fully automated on a 20 min cycle to allow for unattended processing of an entire flight of 72 sample canisters within 30 h, thereby reducing typical sample residence times in the canisters to less than 3 days. The new analytical system is capable of quantifying a wide suite of C2 to C10 organic compounds at part-per-trillion sensitivity. This paper describes the sampling and analysis systems, along with the data analysis procedures which include a new peak-fitting software package for rapid chromatographic data reduction. Instrument sensitivities, uncertainties and system artifacts are presented for 35 trace gas species in canister samples. Comparisons of reported mixing ratios from each field campaign with measurements from other instruments are also presented.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".