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
Abstract This article highlights techniques by which the enantiomers of chiral environmental pollutants can be separated and quantified. A large number of organic chemicals are chiral and exist as pairs of mirror images called enantiomers . These chemicals include legacy persistent organic pollutants (POPs) (e.g. polychlorinated biphenyls (PCBs)) and pesticides (e.g. dichlorodiphenyltrichloroethane (DDT)), as well as current‐use pesticides (e.g. pyrethroids), flame retardants (e.g. hexabromocyclododecane), and pharmaceuticals (e.g. ibuprofen). Understanding the environmental behavior of chiral xenobiotic compounds is important because enantiomers of a chiral compound may have different biological and toxicological effects, which must be delineated for accurate risk assessment of hazards, if any, posed by such chemicals. In addition, chiral chemicals are markers of biochemical activity in the environment, as enantiomer compositions are unaffected by physical and chemical processes but can change from differential enantiomer interactions with other chiral molecules (e.g. enzymes). For these reasons, the chirality of environmental pollutant occurrence, fate, and effects has been studied since the 1990s, when analytical capacity to measure chiral chemicals became widely available. We discuss major techniques for separating pollutant enantiomers including gas chromatography (GC), high‐performance liquid chromatography (HPLC), and capillary electrophoresis (CE). Enantioselective analytical separations are often coupled to mass spectrometry (MS) and tandem mass spectrometry (MS/MS) for quantification under environmentally relevant conditions (i.e. low concentrations to parts per trillion and below, in highly complex matrices such as wastewater and biological tissues). Issues involving sample preparation, data handling, and quality assurance/quality control are also described. Finally, we also illustrate applications of enantiomer‐specific measurements to gain insights into pollutants affecting environmental processes that could otherwise not be obtained, such as assessing pollutant biodegradation and delineating pollutant sources.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.086 | 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