Small-Angle Neutron Scattering to Detect Rafts and Lipid Domains
Bibliographic record
Abstract
The detection and characterization of lateral heterogeneities or domains in lipid mixtures has attracted considerable interest, because of the roles that such domains may play in biological function. Studies on both model and cell membranes demonstrate that domains can be formed over a wide range of length scales, as small as nanometers in diameter up to microns. However, although the size and shape of micron-sized domains are readily visualized in freely suspended vesicles, by techniques such as fluorescence microscopy, imaging of nanometer-sized domains has thus far been performed only on substrate-supported membranes (through, e.g., atomic force microscopy), whereas additional evidence for nanodomains has depended on indirect detection (through, e.g., nuclear magnetic resonance or fluorescence resonance energy transfer). Small-angle neutron scattering (SANS) is a technique able to characterize structural features on nanometer length scales and can be used to probe freely suspended membranes. As such, SANS shows promise to characterize nanometer-sized domains in model membranes. The authors have recently demonstrated the efficacy of SANS to detect and characterize nanodomains in freely suspended mixed lipid vesicles.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".