<sup>17</sup>O MAS NMR Correlation Spectroscopy at High Magnetic Fields
Bibliographic record
Abstract
The structure of two protected amino acids, FMOC- l -leucine and FMOC- l -valine, and a dipeptide, N -acetyl- l -valyl- l -leucine (N-Ac-VL), were studied via one- and two-dimensional solid-state nuclear magnetic resonance (NMR) spectroscopy. Utilizing 17 O magic-angle spinning (MAS) NMR at multiple magnetic fields (17.6–35.2 T/750–1500 MHz for 1 H) the 17 O quadrupolar and chemical shift parameters were determined for the two oxygen sites of each FMOC-protected amino acids and the three distinct oxygen environments of the dipeptide. The one- and two-dimensional, 17 O, 15 N– 17 O, 13 C– 17 O, and 1 H– 17 O double-resonance correlation experiments performed on the uniformly 13 C, 15 N and 70% 17 O-labeled dipeptide prove the attainability of 17 O as a probe for structure studies of biological systems. 15 N– 17 O and 13 C– 17 O distances were measured via one-dimensional REAPDOR and ZF-TEDOR experimental buildup curves and determined to be within 15% of previously reported distances, thus demonstrating the use of 17 O NMR to quantitate interatomic distances in a fully labeled dipeptide. Through-space hydrogen bonding of N-Ac-VL was investigated by a two-dimensional 1 H-detected 17 O R 3 -R-INEPT experiment, furthering the importance of 17 O for studies of structure in biomolecular solids.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".