Small-angle neutron scattering from large unilamellar vesicles: An improved method for membrane thickness determination
Bibliographic record
Abstract
Small-angle neutron scattering (SANS) measurements were performed on large unilamellar vesicles (LUVs) in order to investigate solute effects on membrane properties. Although SANS is a well established technique for the measurement of membrane thickness in unilamellar vesicles, earlier measurements have depended on approximate treatments of the scattering function and have suffered from effects of multilamellarity or difficulty in sample preparation. More recent studies of temperature induced thickness changes in DPPC LUVs which have included explicit treatment of the full scattering function were complicated by disparities between the predicted and measured scattering curves. Here, we reexamine theoretical descriptions of SANS from LUVs. Motivated by our observations, we then introduce a new method for interpretation of SANS data, which we compare to established techniques and apply to our measurements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".