The need to revisit lipid areas
Bibliographic record
Abstract
We have studied the structural properties of lipid bilayers made up of monounsaturated phosphatidylcholines (i.e. diCn:1PC, where n=14, 16, 18, 20, 22 and 24). High-resolution x-ray scattering data were analyzed in conjunction with contrast varied neutron scattering data, using the recently developed technique by Kučerka et al. [Biophys. J. 95, 2356 (2008)]. Analyses of the data show that with increasing n lipid bilayers do not thicken in a linear fashion, as is often assumed, but quadratically, and that lipid area assumes a maximum value for n∼18 bilayers. More importantly, compared to previous data our results strongly suggest that lipid areas are smaller by about 10%. This observation highlights the need to revisit lipid areas as they are extensively used in molecular dynamics simulations and for calibrating their force fields.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.009 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| 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".