Chemical Shift Tensors of Cimetidine Form A Modeled with Density Functional Theory Calculations: Implications for NMR Crystallography
Bibliographic record
Abstract
The principal components of the 13 C chemical shift tensors for the ten crystallographically distinct carbon atoms of the active pharmaceutical ingredient cimetidine Form A have been measured using the FIREMAT technique. Density functional theory (DFT) calculations of 13 C and 15 N magnetic shielding tensors are used to assign the 13 C and 15 N peaks. DFT calculations were performed on cimetidine and a training set of organic crystals using both plane-wave and cluster-based approaches. The former set of calculations allowed several structural refinement strategies to be employed, including calculations utilizing a dispersion-corrected force field that was parametrized using 13 C and 15 N magnetic shielding tensors. The latter set of calculations featured the use of resource-intensive hybrid-DFT methods for the calculation of magnetic shielding tensors. Calculations on structures refined using the new force-field correction result in improved values of 15 N magnetic shielding tensors (as gauged by agreement with experimental chemical shift tensors), although little improvement is seen in the prediction of 13 C shielding tensors. Calculations of 13 C and 15 N magnetic shielding tensors using hybrid functionals show better agreement with experimental values in comparison to those using GGA functionals, independent of the method of structural refinement; the shielding of carbon atoms bonded to nitrogen are especially improved using hybrid DFT methods.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".