Distribution of perfluorocarboxylate isomers in select samples from the north american environment
Bibliographic record
Abstract
Perfluorinated acids are anthropogenic pollutants with primarily two industrial synthetic routes: electrochemical fluorination (ECF) and telomerization. A mixture of structural isomers is produced by ECF, while telomerization conserves the geometry of its starting materials, which are typically linear. To contribute to a discussion on sources of perfluorinated acid pollution, isomer profiles of perfluorinated carboxylates (PFCAs) were determined in a diverse set of environmental and biotic samples from remote to urban locations. Analysis was conducted on the derivatized extracts using gas chromatography/mass spectrometry. The perfluorooctanoate (PFOA) isomer profile in most samples contained linear and branched isomers congruent with an ECF input, but linear PFOA (n-PFOA) predominated (>90%) greater than in the ECF technical product (78%). The perfluorononanoate (PFNA) isomer pattern varied from only n-PFNA, n- and iso-PFNA (isopropyl isomer), or n-PFNA and multiple branched isomers. At midlatitudes, PFNA isomer profiles containing multiple branched isomers are attributed to ECF sources such as impurities in ECF PFOA. In surface water from Lake Ontario (Canada) and an Arctic lake, only n- and iso-PFNA were observed. Human and dolphin blood contained multiple branched PFNA, consistent with an ECF signature albeit n-isomer enriched. Both n- and isopropyl isomers of longer-chain PFCAs were observed with a distinct pattern for dolphin and Arctic samples compared to those from the Lake Ontario ecosystem. These results support the hypothesis that long-range atmospheric transport of linear volatile precursors, subsequent degradation, and deposition contribute to the presence of n-PFCAs in the Arctic freshwater environment. The presence of longer-chain isopropyl isomers may be preliminary evidence of isopropyl fluorinated organic precursors.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".