Improving the simplified‐perturbed‐hard‐chain theory equation of state using a new non‐attracting hard‐sphere equation
Bibliographic record
Abstract
Abstract In this research a new simple non‐attracting hard‐sphere equation is introduced. The equation meets the ideal gas and close‐packed limits and is in accordance with computer simulation data with reasonable accuracy. When this equation is used with the simpli‐fied‐perturbed‐hard‐chain theory equation of state, improvements on the calculation of vapour pressure and saturated liquid density of pure compounds are observed. For 35 pure compounds of different classes, the averages of absolute error are 3.31% and 4.20% for the calculation of vapour pressure and saturated liquid density, respectively. The respected errors for the original equation of state are 3.53% and 4.96%, respectively. Moreover, the use of the new hard‐sphere equation in place of the Carnahan‐Starling equation in the simplified‐perturbed‐hard‐chain theory equation of state, does not have any appreciable effect on the prediction of K factors in VLE calculations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".