Quantification of Steroid Sex Hormones Using Solid‐Phase Extraction Followed by Liquid Chromatography–Mass Spectrometry
Bibliographic record
Abstract
In this study, the occurrence of trace amounts of natural and synthetic steroid estrogens in the aquatic environment was studied using liquid chromatography coupled with electrospray mass spectrometry, following solid-phase extraction (SPE). The SPE was performed with C18 and NH2 cartridges. The first objective was to develop a reliable method for analyzing steroid estrogens (resulting from human and animal excretions) in different matrices. The method developed was then applied to quantify the occurrence of natural and synthetic hormones (estrone [E1], 17beta-estradiol [betaE2], 17alpha-estradiol [alphaE2], estriol [E3], and 17alpha-ethinylestradiol [EE2]) in environmental samples in surface water and wastewater treatment plant (WWTP) influent and effluent. In the WWTP influents, betaE2, alphaE2, and E3 were identified as ranging up to 72.6 ng/L in WWTP influent and to 16 ng/L in WWTP effluent. Analysis o f surface wa ter sampled upstream from the WWTP revealed the presence of all five estrogens, at levels up to 19.8 ng/L. These concentrations of estrogens pose an issue for large and small communities, because they are higher than the recommended guidelines for estrogen-active compounds and because a lot of communities use surface water as drinking-water sources.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".