Automated accurate mass data processing using a gas chromatograph/time‐of‐flight mass spectrometer in drug discovery
Bibliographic record
Abstract
A gas chromatograph/time-of-flight (GCT) mass spectrometer, with high mass measurement accuracy to within 5 ppm, has been used for the automated accurate mass analysis of multicomponent mixtures and drug discovery compounds. A multicomponent mixture was analyzed several times over the course of a week to assess the reproducibility and ruggedness of the automated method while operating the GCT in electron ionization mode. For example, the data for 31 radical cations generated via electron ionization was processed using automated software (i.e. OpenLynx) to provide for mass accuracies less than 5 ppm for nearly 100% of the ions from multiple injection data. Mass accuracies of the radical anions of polyaromatic hydrocarbons generated via negative chemical ionization, and protonated pyridines and quinolines generated via methane chemical ionization, were mainly less than 5 ppm from multiple injection data. In addition, the automated method has been used for the accurate mass analysis of drug discovery compounds.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".