Using measured octanol-air partition coefficients to explain environmental partitioning of organochlorine pesticides
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Octanol-air partition coefficients (Koa) were measured directly for 19 organochlorine (OC) pesticides over the temperature range of 5 to 35 degrees C. Values of log Koa at 25 degrees C ranged over three orders of magnitude, from 7.4 for hexachlorobenzene to 10.1 for 1,1-dichloro-2,2-bis(p-chlorophenyl) ethane. Measured values were compared to values calculated as KowRT/H (where R is the ideal gas constant [8.314 J mol(-1) K(-1)], T is absolute temperature, and H is Henry's law constant) were, in general, larger. Discrepancies of up to three orders of magnitude were observed, highlighting the need for direct measurements of Koa. Plots of Koa versus inverse absolute temperature exhibited a log-linear correlation. Enthalpies of phase transition between octanol and air (deltaHoa) were determined from the temperature slopes and were in the range of 56 to 105 kJ mol(-1) K(-1). Activity coefficients in octanol (gamma(o)) were determined from Koa and reported supercooled liquid vapor pressures (pL(o)), and these were in the range of 0.3 to 12, indicating near-ideal solution behavior. Differences in Koa values for structural isomers of hexachlorocyclohexane were also explored. A Koa-based model was described for predicting the partitioning of OC pesticides to aerosols and used to calculate particulate fractions at 25 and -10 degrees C. The model also agreed well with experimental results for several OC pesticides that were equilibrated with urban aerosols in the laboratory. A log-log regression of the particle-gas partition coefficient versus Koa had a slope near unity, indicating that octanol is a good surrogate for the aerosol organic matter.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.022 | 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 it