Direct Measurement of Trace Elemental Mercury in Hydrocarbon Matrices by Gas Chromatography with Ultraviolet Photometric Detection
Bibliographic record
Abstract
We introduce a technique for the direct measurement of elemental mercury in light hydrocarbons such as natural gas. We determined elemental mercury at the parts-per-trillion level with high precision [<3% RSD (n = 20 manual injection)] using gas chromatography with ultraviolet photometric detection (GC-UV) at 254 nm. Our approach requires a small sample volume (1 mL) and does not rely on any form of sample preconcentration. The GC-UV separation employs an inert divinylbenzene porous layer open tubular column set to separate mercury from other components in the sample matrix. We incorporated a 10-port gas-sampling valve in the GC-UV system, which enables automated sampling, as well as back flushing capability to enhance system cleanliness and sample throughput. Total analysis time is <2 min, and the procedure is linear over a range of 2-83 μg/m(3) [correlation coefficient of R(2) = 0.998] with a measured recovery of >98% over this range.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".