Separation of natural product using columns packed with Fused‐Core particles
Bibliographic record
Abstract
Three HPLC columns packed with 3 microm, sub-2 microm, and 2.7 microm Fused-Core (superficially porous) particles were compared in separation performance using two natural product mixtures containing 15 structurally related components. The Ascentis Express C18 column packed with Fused-Core particles showed an 18% increase in column efficiency (theoretical plates), a 76% increase in plate number per meter, a 65% enhancement in separation speed and a 19% increase in back pressure compared to the Atlantis T3 C18 column packed with 3 microm particles. Column lot-to-lot variability for critical pairs in the natural product mixture was observed with both columns, with the Atlantis T3 column exhibiting a higher degree of variability. The Ascentis Express column was also compared with the Acquity BEH column packed with sub-2 microm particles. Although the peak efficiencies obtained by the Ascentis Express column were only about 74% of those obtained by the Acquity BEH column, the 50% lower back pressure and comparable separation speed allowed high-efficiency and high-speed separation to be performed using conventional HPLC instrumentation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".