Stability of pharmaceuticals and other polar organic compounds stored on polar organic chemical integrative samplers and solid-phase extraction cartridges
Bibliographic record
Abstract
The stability of 24 chemicals, including pharmaceuticals and personal care products, and some agrochemicals on extraction media was evaluated by preloading them onto Oasis hydrophilic lipophilic balanced solid-phase extraction (SPE) cartridges and polar organic chemical integrative samplers (POCIS) followed by storage at -20°C over time. After 20 months, the average loss was 11% on POCIS, with only 2,4-dichlorophenoxyacetic acid, atrazine, chlorpyrifos, and gemfibrozil showing a statistically significant decline compared with initial concentrations. Losses on SPE cartridges were below 19%, with an average loss of 9%. In addition to laboratory spiked samples, multiple POCIS deployed in wastewater-impacted surface waters and SPE extracts of these waters were stored in their original coextracted matrix for nearly two years with minimal observed losses. Errors from typical sampling, handling, and concentration estimates from POCIS sampling rates were typically ± 15 to 30% relative standard deviation, so observed storage losses are minimal for most POCIS applications. While losses during storage on SPE cartridges for 20 months were small but statistically significant for many compounds, addition of labeled internal standards prior to freezing should correct for such losses. Thus, storage of processed water samples for analysis of polar organic pollutants is viable for archival purposes or studies for which samples cannot be analyzed in the short term.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".