Preferential Solvation of Acetaminophen in Propylene Glycol + Water Co-Solvent Mixtures
Bibliographic record
Abstract
The preferential solvation parameters defined as the differences between the local mole fraction of solvents around analgesic drug acetaminophen and those for the bulk co-solvent composition in propylene glycol + water mixtures were derived from their thermodynamic properties by means of the inverse Kirkwood-Buff integrals (IKBI) and the quasi-lattice-quasi-chemical (QLQC) methods. It is found that acetaminophen is sensitive to solvation effects, so according to IKBI method the preferential solvation parameter δ´xPG,A, is negative in water-rich mixtures but positive in medium compositions and in co-solvent-rich mixtures. It is conjecturable that in water-rich mixtures the hydrophobic hydration around the aromatic ring and methyl group present in the drug plays a relevant role in the solvation. The bigger drug solvation by co-solvent in mixtures of similar solvent proportions and in propylene glycol-rich mixtures could be due mainly to polarity effects. Otherwise, according to QLQC method, this drug is preferentially solvated by the co-solvent in all the mixtures.
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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".