On the prediction of surface tension for multicomponent mixtures
Bibliographic record
Abstract
Abstract A prediction method for surface tension of real mixtures was developed based on the Davis theory, and tested with the molecular dynamics simulation results of Mecke et al. (1997) for surface tension of the Lennard‐Jones fluid. An effective Lennard‐Jones potential was introduced for correlating surface tension for real pure liquids and binary liquid mixtures, leading to prediction of surface tension of multicomponent systems, including aqueous mixtures. The overall average absolute percentage deviations (AAPD) obtained in the correlated results for 62 pure liquids, 91 non‐aqueous and 11 aqueous binaries are 0.66, 0.80, and 1.75, respectively. In the prediction of the surface tension for 9 ternary and 4 quaternary systems, using the molecular parameters of pure liquids and the adjustable binary parameters, the overall AAPDs are 1.75 and 1.03, respectively.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".