Nanospray ‘taxation’ and how to avoid it
Bibliographic record
Abstract
In mass spectrometric analysis with nanospray ionization, some analytes were found to appear in spectra with a delay of tens of minutes, while a few others could not be detected at all. The effect was found to be related to cation-exchange chromatography with negative charge on the glass surface, and with the most affected peptide or protein ions having strong localization of positive charge in blocks of two or more adjacent basic amino acid residues (e.g. melittin). The 'affinity' to the glass surface was studied with a peptide mixture and bovine serum albumin (BSA) tryptic digest solutions at sub-micromolar concentration. About 20% fewer tryptic peptides could be identified from spectra recorded with a glass nanospray capillary compared to those acquired with either conventional 1 microL/min electrospray or a quartz nanospray capillary. Protein identification studies are not likely to be seriously affected by this loss, but other protein applications, such as investigations of mutations or post-translational modifications, may suffer due to reduced sequence coverage. Ways to avoid losses of useful ions are discussed.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.013 |
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".