A comparative analysis of empirical equations describing pressure dependence of equilibrium and reaction rate constants
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Bibliographic record
Abstract
General properties of the empirical analytical functions used to describe the effect of pressure on rate and equilibrium constants in solution are reviewed, and the effects of experimental errors on the accuracy of activation and reaction volumes predicted by these equations are compared. When the error levels are low (1%–2%) and pressure ranges are small (0–1 kbar), all functions perform well, but when fitting data with high error or extending to higher pressures, special care must be taken to obtain reliable results. Analysis of the results from fitting the equations to simulated data, as well as experimental data for Diels–Alder, Menshutkin, and methanolysis reactions, allows us to propose a set of general recommendations when using these equations as a tool for obtaining accurate activation and reaction volumes.
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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 | 0.000 | 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 it