An automated, high through‐put method for accurate and precise measurements of dissolved nitrous‐oxide and methane concentrations in natural waters
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract We describe a technique for measuring dissolved CH 4 and N 2 O concentrations from discrete water samples using an automated purge and trap gas extraction system, coupled with a gas chromatograph‐mass spectrometer (PT‐GCMS). The automated system measures blanks, standards, and 25 samples in less than five hours with only ∼ 30 min of operator involvement. Rigorous testing of the PT‐GCMS demonstrates sensitivity, accuracy and precision that is comparable or better than conventional methods for CH 4 and N 2 O analysis. Measured concentrations of CH 4 and N 2 O in air‐equilibrated water samples showed good agreement with expected values derived from solubility calculations, and results of a multilaboratory intercalibration exercise showed that our measurements agree with those made using conventional methods. Precision of replicate water samples is 3.3% for CH 4 and 3.0% for N 2 O. Detection limits are well below the expected concentrations in most natural waters with a five milliliters sample, and can be lowered substantially by analyzing a larger sample volume. To demonstrate the utility of the method, we present depth profiles of CH 4 and N 2 O from Saanich Inlet, a coastal anoxic fjord in British Columbia. The Saanich Inlet water column exhibits rapid changes in CH 4 and N 2 O across depth‐dependent and seasonally variable redox conditions. Our high through‐put, automated method facilitates the measurement of aqueous N 2 O and CH 4 concentrations, and will thus help to improve our understanding of the natural cycling of these climate‐active trace gases.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it