Nuclear magnetic shielding of molecule in solution based on reference interaction site model self-consistent field with spatial electron density distribution
Bibliographic record
Abstract
A new method for calculating nuclear magnetic shielding in solutions is developed based on the reference interaction site model self-consistent field (RISM-SCF) with spatial electron density distribution (SEDD). In RISM-SCF-SEDD, the electrostatic interaction between the solute and the solvent is described by considering the spread of electron to obtain more realistic electronic structure in solutions. It is thus expected to allow us to predict more quantitative chemical shifts of a wide variety of chemical species in solutions. In this study, the method is applied to a water molecule in water and is validated by examining the dependence of the solvent temperature and density on chemical shifts. The dependence of solvent species is also investigated, and more accurate results are obtained for polar solvents compared to the previous RISM-SCF study. Another application example of this method is the 15N chemical shifts of two azines in water, which is difficult to predict with the polarizable continuum model (PCM). Our results are in good agreement with the previous quantum mechanical/molecular mechanics study and experimental results. It is also shown that our method gives more realistic results for methanol and acetone than the PCM.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".