Which of the (Mixed) Halogenated n-Alkanes Are Likely To Be Persistent Organic Pollutants?
Bibliographic record
Abstract
) and the myriad isomers of all possible (mixed) halogenated n-alkanes (PXAs). This study prioritizes the PXAs on the basis of their potential to persist, bioaccumulate, and undergo long-range transport guided by quantitative structure-property relationships (QSPRs), density functional theory (DFT), chemical fate models, and partitioning space. The QSPR results narrow the list to 966 elemental compositions, of which 352 (23 Br, 83 Cl/F, 119 Br/Cl, and 127 Br/F) are likely constituents of substances used as lubricants, plasticizers, and flame retardants. Complementary DFT calculations suggest that an additional 1367 elemental compositions characterized by a greater number of carbon and fluorine atoms but fewer chlorine and bromine atoms may also pose a risk. The results of this study underline the urgent need to identify and monitor these suspected pollutants, most appropriately using mass spectrometry. We estimate that the resolving power required to distinguish ∼74% of the prioritized elemental compositions from the most likely interferents, i.e., chlorinated alkanes, is approximately 60,000 (full width at half-maximum). This indicates that accurate identification of the PXAs is achievable using most high-resolution mass spectrometers.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".