Sub‐2 μm HPLC coupled with sub‐ppm mass accuracy for analysis of pharmaceutical compound libraries
Bibliographic record
Abstract
Recent advances in accurate mass analysis are poised to allow the high-throughput production of accurate mass data on many more compounds than was previously available. It is shown that sub-ppm mass accuracy (producing elemental compositions) can be obtained on a simple TOF mass spectrometer operating in the manufacturer's standard mode. Concomitantly, there have been important technological advances in LC with respect to speed of analysis using sub-2 microm particle columns. Much of the sub-2 microm work in the literature has been under the label ultra performance LC (UPLC), however, we show that very high-speed results can be obtained using other manufacturer's pumps by using elevated column temperatures. Using elevated temperatures, HPLC peak widths on the order of 1 s can be obtained. We report the coupling of these two technologies (sub-ppm mass accuracy MS with high-speed HPLC) for the rapid analysis of compounds entering pharmaceutical libraries.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".