Determination of Vapor Pressures, Octanol−Air, and Water−Air Partition Coefficients for Polyfluorinated Sulfonamide, Sulfonamidoethanols, and Telomer Alcohols
Bibliographic record
Abstract
Liquid-phase vapor pressures ( P L ) and octanol−air partition coefficients ( K OA ) for N- ethyl perfluorooctane sulfonamide, N- methyl perfluorooctanesulfonamidoethanol, N- ethyl perfluorooctanesulfonamidoethanol, and four fluorotelomer alcohols (CF 3 (CF 2 ) n CH 2 CH 2 OH, n = 3, 5, 7, and 9) were estimated as a function of temperature using a technique based on measuring gas chromatographic retention times relative to those of hexachlorobenzene. The method was calibrated using volatility data for fluorinated aromatic substances, chlorinated benzenes, and pesticides. The fluorinated telomer alcohols were found to have a volatility higher than that of the nonfluorinated alcohols of similar chain length and higher than that of perfluorinated aromatics of comparable molar mass. On the basis of their volatility, the polyfluorinated chemicals are expected to occur predominantly in the atmospheric gas phase. The water−air partition coefficient ( K WA ) for the three shorter carbon chain length fluorotelomer alcohols was determined as a function of temperature using equilibrium static headspace gas chromatography and the phase ratio variation method. The K WA values of the three fluorinated telomer alcohols extrapolated to 25 °C are of a similar order of magnitude (1 < log K WA < 2) and suggest that rain scavenging is not a very efficient atmospheric deposition process.
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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 | 0.000 | 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".