Correlating environmental partitioning properties of organic compounds: The three solubility approach
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
Abstract It is suggested that in addition to correlating the environmental partitioning characteristics of chemicals as partition coefficients, it is also valuable to correlate them as solubilities or pseudo-solubilities. These solubilities are essentially convenient, readily understood, and in many cases, measurable expressions of single-phase activity coefficients. To illustrate this approach, a novel, three solubility, quantitative structure-property relationships (or QSAR) approach is described for correlating the physico-chemical parameters in which the solubilities or pseudo-solubilities of individual chemicals in the liquid or super-cooled liquid state, both individually and as homologous series, are compiled and correlated as a function of temperature in the three primary media of air, water, and octanol and possibly in other relevant media. These quantities, which are deduced from measured partition coefficients, solubilities, and vapor pressures, comprise a consistent data set that can be used to estimate a variety of environmentally relevant partition coefficients. The approach is demonstrated in detail for the chlorobenzenes and in a preliminary fashion for a variety of persistent and hydrophobic substances. The merits of this approach as a supplement to the conventional use of partition coefficients are discussed.
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) | 0.013 | 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