Expanding the Applicability Range of the Generator Column Technique to Measure the Octanol–Air Partition Ratio of Volatile Compounds
Bibliographic record
Abstract
Bioaccumulation modeling has identified a lower limit of ∼5 for the log of the octanol–air partition ratio (log K OA ) of chemicals that potentially bioaccumulate in air-breathing organisms. Because existing techniques are not well suited to this volatility range (vapor pressure between 1 and 1000 Pa), we adjusted the generator column method to allow for K OA determination of more volatile compounds. We reduced gas flow rates and experimental run times and examined the potential depletion of octanol within the generator column. By recording K OA values for hexachlorobenzene, 1,2,3,4-tetrachlorobenzene, and 1,2,3-trichlorobenzene that agree with earlier measurements, we first confirmed our ability to obtain reliable data with the generator column technique. The log K OA values between 5 and 45 °C for 1,3-dichlorobenzene, trans -decalin, 2,6-dimethyldecane, 1,2,3,4-tetramethylbenzene, hexylcyclohexane, tri-isopropyl phosphate, and tetradecene have been obtained with the technique. The lowest log 10 K OA value measured was 4.6 9 for trans -decalin at 25 °C. Good agreement with predictions made with poly-parameter linear free energy relationships lends confidence to these data. Reducing gas flow rates and experimental run times are key to obtaining reliable K OA data when applying the generator column technique to volatile compounds. Depletion of the octanol concentration in the generator column did not notably affect the K OA obtained from the measurements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".