Development of a thermodynamic model of aqueous solution suited for foods and biological media. Part B: Prediction of standard formation properties
Bibliographic record
Abstract
Abstract In food and biological processes, aqueous complexes cover a wide diversity of species and the presence of several phases. The modelling of such processes must take into account these specificities, which require a generalization of the existing thermodynamic models of aqueous solutions. The chemical potential (the molar Gibbs free energy) of a given compound is an important variable to characterize the physical‐chemical properties at equilibrium. Its value depends on two parameters: the Gibbs free energy of formation and the activity coefficient. Both are linked to a chosen reference state. Then, the main thermodynamic modelling task consists in the prediction and/or the collection of formation properties data and in the development of a predictive model of activity coefficients. In this study, a method of prediction of the gas phase formation properties of several organic molecules of interest in foods and biological media using the same input data as those of the COSMO‐RS model (i.e., results of quantum DFT/COSMO calculations) is introduced. This kind of fully predictive approach allows the treatment of conformations. This is its main advantage compared to classical group contribution methods. For fifteen of the studied molecules, the Gibbs free energies of formation predicted at infinite dilution in water are also calculated and compared to experimental data.
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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".