Metrologically traceable quantification of trifluoroacetic acid content in peptide reference materials by<sup>19</sup>F solid-state NMR
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Bibliographic record
Abstract
Although solution-state NMR is frequently used in metrologically-traceable quantification studies, this is not the case for solid-state NMR. However, solid-state NMR allows quantification of substances without the need of dissolution, providing a truly non-destructive approach, and extending metrologically-traceable quantitative NMR to sample classes that are difficult to characterize in solution. In this contribution we present a thorough and rigorous protocol for ¹⁹F quantitative solid-state NMR employing a certified reference material as external calibrant to provide metrological traceability to absolutely quantify the content of trifluoroacetic acid (TFA) in a peptide sample, typically the major impurity in synthetic peptides. The protocol includes determining the quantitative volume of the solid-state NMR sample holder (rotor), the ERETIC (electronic reference to access in vivo concentrations) method (Akoka et al 1999 Anal. Chem. 71 2554) to compensate for variations in the sensitivity of the radio frequency resonant circuit when an external calibrant is used, and the EASY (elimination of artefacts in NMR spectroscopy) method (Jaeger and Hemmann 2014 Solid State Nucl. Magn. Reson. 57–58 22) to effectively suppress the ¹⁹F NMR background signal from the probe head. We applied the protocol to quantify the amount of TFA in a candidate NRC certified reference material of the peptide angiotensin II. The results obtained by ¹⁹F quantitative solid-state NMR are in excellent agreement with those obtained by quantitative NMR in solution employing an internal calibrant.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 it