Chemical ionization pathways of polyfluorinated chemicals—A connection to environmental atmospheric processes
Bibliographic record
Abstract
A systematic mass spectrometry study of an industrially prolific class of polyfluorinated compounds known as telomers was conducted. The study specifically focused upon polyfluorinated alcohols along with corresponding saturated and alpha,beta-unsaturated fluoroacids. Within each class differing fluoroalkyl chain length homologues were investigated, using negative and positive chemical ionization mass spectrometry (NCI and PCI). In the case of the fluoroalcohols, NCI resulted in the production of more elaborate spectra than the other classes. Moreover, it showed the interesting production of HF(2)(-) and the complex of this species, along with F(-), with the parent molecule. These complexes resulted in the formation of the novel H(2)F(3)(-) ion. Results show that there is significant intra-molecular hydrogen bonding that occurs for these compounds, which influences the molecules fragmentation. This bonding will also influence the fate and disposition through environmental processes (e.g., V(P), k(OH), K(OW), K(OA)) which are affected by molecular geometry. Furthermore, there is an increased accumulation and persistence potential for the molecule as a function of the fluorocarbon chain length. We have shown that in conjunction with the use of mass spectroscopy the engertics of environmental processes for polyfluorinated materials can be established.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".