Discrimination in racemates of small chiral molecules
Bibliographic record
Abstract
A comparison of similar chiral molecules provides information about the impact of molecular characteristics on selectivity. In this article, the intermolecular structure in racemic fluids is the basis for comparing the molecules: the radial distribution between atoms on identical molecules is compared with the corresponding distribution for atoms from a mirror-image pair. A difference in these distributions signals an enantiomeric imbalance in the local distribution of molecules. The structure in the racemic fluids is explored using Monte Carlo (MC) simulations and the integral equation theory of Chandler, Silbey and Ladanyi (CSL) [1982, Molec. Phys., 46, 1335]. Racemic fluids are examined for several categories of chiral molecules. First, symmetrically shaped molecules have been considered in order to isolate local excesses attributable to energetic contributions. Second, racemates of hard chiral molecules have been examined. Here, enantiomeric imbalances can only originate from asymmetry in the molecular shape. Finally, both the molecular shape and the interaction strengths have been varied in order to explore the competition between steric and energetic effects. Within each category, the number of chiral molecules is large and a selection mechanism is required to identify those molecules which are expected to show large local excesses. An appropriate selection criterion (chirality index) has been defined and evaluated for 400 000 chiral molecules. Based on the results of this assessment, 24 racemates have been chosen for detailed examination by MC simulations and integral equation theories.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".