Bibliographic record
Abstract
The structure in four racemic fluids is explored using two integral equation theories: the reference interaction site method (RISM) [D. Chandler and H. C. Andersen, J. Chem. Phys. 57, 1930 (1972)] and the diagrammatically correct theory of Chandler, Silbey, and Ladanyi (CSL) [D. Chandler, R. Silbey, and B. M. Ladanyi, Mol. Phys. 46, 1335 (1982)]. Discrimination is measured by comparison of site pair distributions for sites on identical molecules with the corresponding distributions for sites on mirror-image molecules. We find that discrimination is largest for distributions between the smallest sites in the molecules. Between racemates, those consisting of more asymmetrical chiral molecules (i.e., with a bigger range of site sizes and bond lengths) show the largest discrimination. The indirect correlation function is shown to be nondiscriminating in racemates. Further, exact relationships between like–like and like–unlike differences in the other pair functions have been obtained. From these, the importance of the bridge functions in discrimination is evident. The CSL theory always satisfies the exact relationships, even with approximate bridge diagrams. RISM theory cannot satisfy these exact limits regardless of density and closure relation. We have found that RISM theory predicts qualitatively incorrect pair distributions at low densities, but that the difference in the distributions is more accurate. All bridge diagrams which contribute to O(ρo) have been enumerated and evaluated. Inclusion of these diagrams into the CSL theory leads to exact results at low density. However, we find that the inclusion of the ρo diagrams has dramatically improved the quality of the CSL theory at all densities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".