Reply to “Comment on ‘Determination and Correlation of Dipyridamole <i>p</i>-Toluene Sulfonate Solubility in Seven Alcohol Solvents and Three Binary Solvents’”
Bibliographic record
Abstract
The Comment on “Determination and Correlation of Dipyridamole p -Toluene Sulfonate Solubility in Seven Alcohol Solvents and Three Binary Solvents” is appreciated. According to the comments, we make a deep analysis and discussion of our article again. The reason for large deviations between the back-calculated value presented in our paper and the back-calculated value calculated by Acree is that we mixed up the coefficients calculated by two programs and the wrong Apelblat equation coefficients were submitted in our paper instead of the corrected ones. Therefore, the model parameters of the Apelblat equation and the calculated mole fraction solubilities of dipyridamole p -toluene sulfonate in all solvents at the temperature ranging from 288.15 to 328.15 K were recalculated by the corrected program and show satisfactory correlation results with the experimental values.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.030 | 0.029 |
| Insufficient payload (model declined to judge) | 0.007 | 0.011 |
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".