Correct Way of Reporting Results when Modelling Supercritical Phase Equilibria using Equations of State
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Bibliographic record
Abstract
Different forms found in the literature to express the error between calculated phase equilibrium variables using equation of state models and experimental data are analyzed in this note. High pressure PTxy data of binary mixtures containing supercritical carbon dioxide are used as study cases. The common practise of using the solvent concentration, instead of the solute concentration, to analyze the accuracy of a thermodynamic model is critically discussed. Several statistical parameters usually employed in the literature are considered to be misleading and it is shown that they do not give a clear indication about how accurate are the model results. Dans cet article, on a analysé différentes formes trouvées dans la littérature pour exprimer l'erreur entre les variables d'équilibre de phases calculées utilisant des modèles d'équation d'état et des données expérimentales. Des données PTxy de pressions élevées pour des mélanges binaires contenant du dioxyde de carbone supercritique sont utilisées comme études de cas. La pratique commune d'utiliser la concentration de solvant au lieu de la concentration de soluté pour analyser la précision d'un modèle thermodynamique est examinée de manière critique. Plusieurs paramètres statistiques habituellement employés dans la littérature scientifique sont considérés comme trompeurs et on montre qu'ils ne donnent pas une indication claire du degré de précision des résultats des modèles.
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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 | 0.001 | 0.001 |
| 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 it