Non-Contact Universal Sample Presentation for Room Temperature Macromolecular Crystallography Using Acoustic Levitation
Bibliographic record
Abstract
Macromolecular Crystallography is a powerful and valuable technique to assess protein structures. Samples are commonly cryogenically cooled to minimise radiation damage effects from the X-ray beam, but low temperatures hinder normal protein functions and this procedure can introduce structural artefacts. Previous experiments utilising acoustic levitation for beamline science have focused on Langevin horns which deliver significant power to the confined droplet and are complex to set up accurately. In this work, the low power, portable TinyLev acoustic levitation system is used in combination with an approach to dispense and contain droplets, free of physical sample support to aid protein crystallography experiments. This method facilitates efficient X-ray data acquisition in ambient conditions compatible with dynamic studies. Levitated samples remain free of interference from fixed sample mounts, receive negligible heating, do not suffer significant evaporation and since the system occupies a small volume, can be readily installed at other light sources.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".