Time-Weighted Average Water Sampling with a Solid-Phase Microextraction Device
Bibliographic record
Abstract
A fiber-in-needle SPME device was developed and investigated for time-weighted average water sampling. The device was designed so that the overall mass-transfer resistance is contained within the static water inside the needle, which ensures that mass uptake could be predicted with Fick's first law of diffusion and the sampling rate is less affected by water turbulence. The device possesses all of the advantages of commercialized devices, in addition to needle filling and replacement ease. Laboratory calibration with deployment of the device to a flow-through system demonstrated that there was a linear mass uptake for up to 12 days, and the linear range could be longer. PDMS coating is assumed to be a perfect zero sink for most polycyclic aromatic hydrocarbons, except naphthalene. The effect of water temperature was also investigated. Under normal field conditions, the change of mass uptake rate with temperature was negligible. To facilitate the convenience for long-term water sampling, a new standard aqueous generator was introduced. This study extended the application of SPME technology for long-term water sampling.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".