The Correlation and Prediction of Butane/Water and Gas/Butane Partition Coefficients
Bibliographic record
Abstract
It has been pointed out previously that the butane/water partition coefficient is a key parameter in the determination of extraction affinity. We have taken 43 such partition coefficients and have obtained a very satisfactory correlation with Abraham solvation parameters. Similarly, we have obtained a good correlation of 43 gas/butane partition coefficients. These correlations are general, and can be used to predict further values of the butane/water and gas/butane partition coefficient. Des études précédentes ont montré que le coefficient de séparation butane/eau est un paramètre clé dans la détermination de l'affinité de l'extraction. Nous avons pris 43 de ces coefficients de séparation et obtenu une corrélation très satisfaisante avec des paramètres de solvatation d'Abraham. De la même manière, nous avons obtenu une bonne corrélation des 43 coefficients de séparation gaz/butane. Ces corrélations sont générales et peuvent permettre de prédire d'autres valeurs du coefficient de séparation butane/eau et gaz/butane.
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How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".