Multinuclear Solid-State Nuclear Magnetic Resonance and Density Functional Theory Characterization of Interaction Tensors in Taurine
Bibliographic record
Abstract
A variety of experimental solid-state nuclear magnetic resonance (NMR) techniques has been used to characterize each of the elements in 2-aminoethane sulfonic acid (taurine). A combination of (15)N cross-polarization magic angle spinning (CPMAS), (14)N ultrawideline, and (14)N overtone experiments enabled a determination of the relative orientation of the nitrogen electric field gradient and chemical shift tensors. (17)O spectra recorded from an isotopically enriched taurine sample at multiple magnetic fields allowed the three nonequivalent oxygen sites to be distinguished, and NMR parameters calculated from a neutron diffraction structure using density functional theory allowed the assignment of the (17)O parameters to the correct crystallographic sites. This is the first time that a complete set of (17)O NMR tensors are reported for a sulfonate group. In combination with (1)H and (13)C MAS spectra, as well as a previously reported (33)S NMR study, this provides a very broad set of NMR data for this relatively simple organic molecule, making it a potentially useful structure on which to test DFT calculation methods (particularly for the quadrupolar nuclei (14)N, (17)O, and (33)S) or NMR crystallography approaches.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.001 | 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 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".