Revealing the parameters to design the habit modifiers for rock-salt crystals: empirical to rational approach
Bibliographic record
Abstract
Morphology of rock-salt crystals can be influenced by internal and external factors like temperature, super saturations, solvent, and impurities. Many impurities and additives have been reported to date for the habit modification of common salt; however, the selection of such impurities is largely empirical. The partition coefficient or log P, which is a measure of hydrophobic hydrophilic property of a material, very aptly signifies the ability of additives to modulate the morphology of sodium chloride crystals. Application of the partition coefficient of additives led to the discovery of two new habit modifiers (cytosine and DMSO) for rock-salt crystals. The predicted results have been verified by experimental studies. Furthermore, the known habit modifiers and also the nonhabit modifiers for sodium chloride crystals corroborate the importance of this parameter to define the morphology of salt crystals. This study is of fundamental importance, which otherwise was rather empirical for the last two centuries.
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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 | 0.001 | 0.002 |
| 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 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".