Bibliographic record
Abstract
Classical kinetic theory has been traditionally applied for calculating the rate of evaporation, but recent results have indicated an inconsistency in this theoretical approach. A new method based on Statistical Rate Theory (SRT) for predicting the evaporation rate has been recently proposed. The method has been applied to predict the evaporation rate with surprising results. It is predicted that the evaporation rate is highly sensitive to the vapour-phase pressure. An experimental apparatus has been constructed to study this prediction. It is found that the evaporation rate from half closed capillaries in a container that includes a bulk liquid phase varies as a function of interface position within the capillaries. The interface position variation corresponds to a pressure difference at the interfaces in the order of magnitude of mPa; still, the evaporation rates are measurably different. The accuracy of the SRT expression for predicting the rate of evaporation may be examined by comparing the predicted vapour-phase pressure to that measured. Since the pressure can not be measured directly with an accuracy greater than approximately 3 Pa, a new method to determine the vapour-phase pressure is proposed. The validity of the method is established in two experiments under completely different environments. The vapour-phase pressure determined from this method was then used to examine the predicted pressure from the SRT. The agreement between the two pressures was within 4 mPa which is four orders of magnitude better than has been reported before.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 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".