Time-dependent integrity during storage of natural surface water samples for the trace analysis of pharmaceutical products, feminizing hormones and pesticides
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Monitoring and analysis of trace contaminants such as pharmaceuticals and pesticides require the preservation of the samples before they can be quantified using the appropriate analytical methods. Our objective is to determine the sample shelf life to insure proper quantification of ultratrace contaminants. To this end, we tested the stability of a variety of pharmaceutical products including caffeine, natural steroids, and selected pesticides under refrigerated storage conditions. The analysis was performed using multi-residue methods using an on-line solid-phase extraction combined with liquid chromatography tandem mass spectrometry (SPE-LC-MS/MS) in the selected reaction monitoring mode. After 21 days of storage, no significant difference in the recoveries was observed compared to day 0 for pharmaceutical products, while for pesticides, significant losses occurred for DIA and simazine after 10 days (14% and 17% reduction respectively) and a statistically significant decrease in the recovery was noted for cyanazine (78% disappearance). However, the estrogen and progestogen steroids were unstable during storage. The disappearance rates obtained after 21 days of storage vary from 63 to 72% for the feminizing hormones. Overall, pharmaceuticals and pesticides seem to be stable for refrigerated storage for up to about 10 days (except cyanazine) and steroidal hormones can be quite sensitive to degradation and should not be stored for more than a few days.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it