Evaluation of column temperature as a means to alter selectivity in the cation exchange separation of alkali metals, alkaline earth metals and amines
Bibliographic record
Abstract
The merits of varying column temperature in a cation exchange separation of alkali metals, alkaline earth metals and amines are considered. Increasing the column temperature (up to 60 degrees C) reduced the retention of all cations, but by varying extents. Consequently, selectivity changes were seen, with reversals in elution order in some cases. To ascertain when temperature is most useful as a separation aid, analytes were classed into three groups according to their temperature behaviour: alkali metals; alkaline earth metals; and amines. Adjusting the column temperature caused selectivity changes between analytes in different groups, but no selectivity changes occurred between analytes in the same group. Further, temperature was compared to the addition of modest amounts of acetonitrile as another means to alter selectivity. The benefits of elevated temperature were not just limited to selectivity changes. Improvements in the efficiencies of all analytes were noted at 60 degrees C. This was especially true for the amines which are severely tailed at ambient temperatures.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".