Environmental analysis by inductively coupled plasma spectrometry: an interesting journey at Queen’s University
Bibliographic record
Abstract
A review of environmental analysis work carried out by the Beauchemin group using inductively coupled plasma (ICP) mass spectrometry (MS) and optical emission spectrometry (OES) over several decades is presented. Using a continuous online leaching method (COLM) with real-time detection by ICPMS allows measurement of the bio-accessibility of elements and can also be used to infer their source. Indeed, unlike batch methods typically used to measure bio-accessibility, the temporal profiles generated with the COLM can readily reveal if different sources of elements are present through several peaks in the temporal profiles. Common sources of different elements can also be revealed through correlations between their temporal profiles. Similarly, Pb isotope ratios obtained as the slope of the linear correlation between the temporal profiles of two Pb isotope can reveal the presence of Pb from tetraethyllead previously employed as antiknock agent in gasoline. Electrothermal vaporization (ETV) coupled to ICPOES allows for the quick analysis of solid samples, eliminating the need for time-consuming digestion. It was successfully applied to the quick quantitative analysis of a variety of environmental samples. This includes clays and soil samples collected during geochemical exploration to locate undercover ore deposits. There is also potential for the direct speciation analysis of solid samples using ETV-ICPOES.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".