Development of a Particle-Trap Preconcentration-Soft Ionization Mass Spectrometric Technique for the Quantification of Mercury Halides in Air
Bibliographic record
Abstract
Measurement of oxidized mercury, Hg(II), in the atmosphere poses a significant analytical challenge as Hg(II) is present at ultra-trace concentrations (picograms per cubic meter air). Current technologies are sufficiently sensitive to measure the total Hg present as Hg(II) but cannot determine the chemical speciation of Hg(II). We detail here the development of a soft ionization mass spectrometric technique coupled with preconcentration onto nano- or microparticle-based traps prior to analysis for the measurement of mercury halides in air. The current methodology has comparable detection limits (4-11 pg m(-3)) to previously developed techniques for the measurement of total inorganic mercury in air while allowing for the identification of HgX2 in collected samples. Both mercury chloride and mercury bromide have been sporadically detected in Montreal urban and indoor air using atmospheric pressure chemical ionization-mass spectrometry (APCI-MS). We discuss limitations and advantages of the current technique and discuss potential avenues for future research including quantitative trace measurements of a larger range of mercury compounds.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".