Two- and Three-Dimensional <sup>13</sup>C–<sup>17</sup>O Heteronuclear Correlation NMR Spectroscopy for Studying Organic and Biological Solids
Bibliographic record
Abstract
We report two- and three-dimensional (2D and 3D) 13 C– 17 O heteronuclear correlation solid-state NMR experiments under magic-angle spinning (MAS) conditions. These experiments utilize the D-RINEPT (Dipolar-mediated Refocused Insensitive Nuclei Enhanced by Polarization Transfer) scheme with symmetry-based SR4 1 2 recoupling blocks for coherence transfer between 13 C and 17 O nuclei. First, a 2D 17 O → 13 C correlation experiment was performed for the [1- 13 C, 17 O]-Gly/Gly·HCl cocrystal and [U- 13 C, 1- 17 O]-α/β- d -glucose samples. Second, a 2D 17 O → 13 C MQ-D-RINEPT correlation experiment where the indirect dimension incorporates the multiple-quantum MAS (MQMAS) scheme was tested for obtaining isotropic 17 O resolution with [U- 13 C, 1- 17 O]-α/β- d -glucose. Third, a new 3D 17 O → 13 C → 13 C correlation experiment was demonstrated where 17 O → 13 C and 13 C → 13 C correlations are achieved by D-RINEPT and DARR (Dipolar Assisted Rotational Resonance) sequences, respectively (thus termed as a 3D D-RINEPT/DARR OCC experiment). This new 3D 17 O NMR experiment is implemented with the aim for site-resolved solid-state 17 O NMR studies.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".