Time-Weighted Average Water Sampling in Lake Ontario with Solid-Phase Microextraction Passive Samplers
Bibliographic record
Abstract
In this study, three types of solid-phase microextraction (SPME) passive samplers, including a fiber-retracted device, a polydimethylsiloxane (PDMS)-rod and a PDMS-membrane, were evaluated to determine the time weighted average (TWA) concentrations of polycyclic aromatic hydrocarbons (PAHs) in Hamilton Harbor (the western tip of Lake Ontario, ON, Canada). Field trials demonstrated that these types of SPME samplers are suitable for the long-term monitoring of organic pollutants in water. These samplers possess all of the advantages of SPME: they are solvent-free, sampling, extraction and concentration are combined into one step, and they can be directly injected into a gas chromatograph (GC) for analysis without further treatment. These samplers also address the additional needs of a passive sampling technique: they are economical, easy to deploy, and the TWA concentrations of target analytes can be obtained with one sampler. Moreover, the mass uptake of these samplers is independent of the face velocity, or the effect can be calibrated, which is desirable for long-term field sampling, especially when the convection conditions of the sampling environment are difficult to measure and calibrate. Among the three types of SPME samplers that were tested, the PDMS-membrane possesses the highest surface-to-volume ratio, which results in the highest sensitivity and mass uptake and the lowest detection level.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".