Rapid Analysis of Dissolved Methane, Ethylene, Acetylene and Ethane using Partition Coefficients and Headspace-Gas Chromatography
Why this work is in the frame
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Bibliographic record
Abstract
Analysis of dissolved methane, ethylene, acetylene, and ethane in water is crucial in evaluating anaerobic activity and investigating the sources of hydrocarbon contamination in aquatic environments. A rapid chromatographic method based on phase equilibrium between water and its headspace is developed for these analytes. The new method requires minimal sample preparation and no special apparatus except those associated with gas chromatography. Instead of Henry's Law used in similar previous studies, partition coefficients are used for the first time to calculate concentrations of dissolved hydrocarbon gases, which considerably simplifies the calculation involved. Partition coefficients are determined to be 128, 27.9, 1.28, and 96.3 at 30°C for methane, ethylene, acetylene, and ethane, respectively. It was discovered that the volume ratio of gas-to-liquid phase is critical to the accuracy of the measurements. The method performance can be readily improved by reducing the volume ratio of the two phases. Method validation shows less than 6% variation in accuracy and precision except at low levels of methane where interferences occur in ambient air. Method detection limits are determined to be in the low ng/L range for all analytes. The performance of the method is further tested using environmental samples collected from various sites in Nova Scotia.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| 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