The structure of the enigmatic ripple phase in saturated bilayers resolved: Machine learning reveals four lipid populations
Bibliographic record
Abstract
Abstract A new mixed radial-angular, three-particle correlation function method in combination with unsupervised machine learning (ML) was applied to examine the emergence of the ripple phase in dipalmitoyphosphatidylcholine (DPPC) lipid bilayers using data from atomistic molecular dynamics (MD) simulations of system sizes ranging from 128 to 4,096 lipids. Based on the acyl tail conformations, the analysis revealed the presence of four distinct conformational populations of lipids in the ripple phases of the DPPC lipid bilayers. The expected gel- (ordered; L o ) and fluid-like (disordered; L d ) lipids are found along with their splayed tail equivalents ( L o,s and L d,s ). These lipids differ based on their gauche distribution and tail packing. The disordered ( L d ) and disordered splayed ( L d,s ) lipids spatially cluster in the ripple in the groove side, that is, in an asymmetric manner across the bilayer leaflets. The ripple phase does not contain large numbers of L d lipids, instead they only exist on the interface of the groove side of the undulation. The bulk of the groove side is a complex coexistence of L o , L o,s and L d,s lipids. The convex side of the undulation contains predominantly L o lipids. Thus, the structure of the ripple phase is neither a simple coexistence of ordered and disordered lipids nor a coexistence of ordered interdigitating gel-like ( L o ) and ordered splayed ( L o,s ) lipids, but instead a coexistence of an ordered phase and a complex mixed phase. Principal component analysis (PCA) further confirmed the existence of the four lipid groups.
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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 | 0.001 |
| 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 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".