Mechanical resolution of chiral objects in achiral media: Where is the size limit?
Bibliographic record
Abstract
Macroscopic chiral objects (boats and planes with turned rudders, shoes, etc.) get separated from their mirror-image counterparts by motion in achiral media. However, chiral molecules are not enantio-differentiated without the presence of a chiral environment, which may be due to other chiral molecules in the medium. This article explores the reasons of this micro/macro difference as well as the size borderline between the two regimes. There are two major demarcation lines, both related to the object's chaotic thermal motion. The first one is due to destruction of the necessary spatial orientation by the fast rotational diffusion. Only particles larger than 1 μm can maintain their original orientation for 1 sec or longer. For smaller particles, an additional external orienting factor, e.g., a strong electric field has to be applied. The second limitation is defined by the ratio of the hydrodynamic separation of the enantiomers (which is directly proportional to time) to their displacement due to the translational Brownian motion (which is proportional to square root of time). On the laboratory time scales (up to a year), the chiral objects have to be larger than 0.25 μm to be resolved. On evolutionary time scales, much smaller object could be resolved. For enantiomers approaching the molecular size, periods comparable to the age of the universe would be required.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".