THE CONFORMATIONAL LANDSCAPE OF PERILLYL ALCOHOL REVEALED BY BROADBAND ROTATIONAL SPECTROSCOPY AND THEORETICAL MODELING
Bibliographic record
Abstract
Perillyl alcohol (PA) is a naturally occurring dietary monoterpene that can be extracted from various plants, such as lavender and peppermint, and its application to human cancer treatment has been explored.$^{1}$ The rotational spectrum of PA has been investigated using a chirped-pulse Fourier transform microwave (FTMW) spectrometer and a cavity FTMW spectrometer. In parallel, we have carried out extensive conformational searches by scanning relevant dihedral angles and also using a semi-classical conformational search program, GFN-xTB.$^{2}$ In total, 108 conformers have been identified and confirmed to be true minima with the subsequent DFT calculations. The relative stabilities of the conformers identified and the interconversion barriers among them have been explored at the MP2/6-311++G(2d,p) and B3LYP-D3(BJ)/def2-TZVP levels of theory. Experimentally, 8 conformers have been assigned and the missing low energy conformers have been rationalized in terms of conformational conversion barriers under a jet expansion condition. A comprehensive study on the conformational distribution of PA may facilitate our understanding of its structural property and possible structural-functional relationship.\n\n1 T. C. Chen, C. O Da Fonseca, A. H Schönthal. Am. J. Cancer Res. 2015, 5, 1580.\n2. S. Grimme, C. Bannwarth, P. Shushkov, J. Chem. Theo. Comput. 2017, 13, 1989.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".