Computational approaches may underestimate pK<sub><i>a</i></sub>values of longer-chain perfluorinated carboxylic acids: Implications for assessing environmental and biological effects
Bibliographic record
Abstract
Acidity constants were calculated using the semiempirical PM6 pK(a) estimation method for all C(2) through C(9) perfluoroalkyl carboxylate (PFCA) congeners and the straight-chain C(10) through C(13) isomers. According to the PM6 estimates, the linear congeners within each PFCA homologue group have the highest pK(a) values by up to 6 units depending on the degree of branching in the perfluoroalkyl chain. In general, the higher the degree of branching in the perfluoroalkyl chain within a homologue group, the lower the estimated pK(a) value. When the branching is closest to the terminal carboxylate group, the effect on the calculated pK(a) is greatest. Although the PM6 calculated pK(a) values agree well with previously reported estimates for selected linear PFCA congeners using the SPARC and COSMOtherm approaches, all computational approaches only show good agreement with reported experimental values for short chain PFCAs (C(2) through C(5)). Increasing divergences are observed between calculated and experimental results by up to several pK(a) units as the perfluoroalkyl chain length increases beyond C(5). The findings demonstrate a need for additional experimental pK(a) measurements for an expanded set of both linear and branched PFCA congeners to confirm previous experimental reports that are potentially in error, and upon which to calibrate existing computational methods and environmental, toxicological, and waste treatment method models.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".