Mass spectrometry applied to the analysis of estrogens in the environment
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
Environmental analytical chemistry has recently changed focus from analysis of non-polar, persistent contaminants (e.g. polychlorinated biphenyls and dioxins) to more polar and labile compounds that interfere with biological processes. For example, natural and synthetic estrogens and their metabolites have been detected in sewage treatment plant effluents at nanogram/liter concentrations that are similar to those at which both total sex reversal and intersex (containing both testes and ova) is induced in fish exposed to these compounds in laboratory experiments. The development of techniques for the analysis of natural and synthetic estrogens in biological fluids (i.e. serum and urine) has been a priority in the biomedical field. However, the recent recognition that estrogen hormones are contaminants in the environment that may contribute to endocrine disruption has focused attention on the need for highly sensitive and specific techniques that are applicable for trace analysis in complex environmental matrices. Three optimized mass spectrometric protocols have been developed for the determination and quantitation of steroid hormones in environmental matrices using gas chromatography/tandem mass spectrometry (GC/MS/MS), liquid chromatography/mass spectrometry selected ion monitoring, (LC/MS - SIM) and liquid chromatography/tandem mass spectrometry (LC/MS/MS). The advantages and disadvantages of each method are presented.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| 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 it