Prediction of the Kinematic Viscosity of Multicomponent Liquid Mixtures: A Generalized McAllister Four-Body Interaction Model and Its Truncation into a <i>Pseudo</i>-Binary Model
Bibliographic record
Abstract
The prediction of the dependence of viscosity on composition is required in many instances in engineering calculations, especially those required for an equipment design. The present communication reports the development of a generalized McAllister four-body interaction for predicting the dependence of viscosities of nonelectrolyte liquid multicomponent systems on composition. The authors also utilized the pseudo -binary model and incorporated it into the McAllister model in order to reduce the number and complexity of parameter calculations at a relatively small expense of the accuracy of predictions. The results clearly show that the four-body interaction model performs better than the generalized McAllister three-body collision model reported earlier by Nhaesi and Asfour. The four-body model performs better for cases where the molecular size ratio between the smallest and largest components in a system exceeds 1.5.
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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 | 0.001 | 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 | 0.001 |
| 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".