Bibliographic record
Abstract
The fusion of biological membranes results in two bilayer-based membranes merging into a single membrane. In this process the lipids have to undergo considerable rearrangement. The nature of the intermediates that are formed during this rearrangement has been investigated. Certain fusion proteins facilitate this process. In many cases short segments of these fusion proteins have a particularly important role in accelerating the fusion process. Studies of the interaction of model peptides with membranes have allowed for increased understanding at the molecular level of the mechanism of the promotion of membrane fusion by fusion proteins. There is an increased appreciation of the roles of several independent segments of fusion proteins in promoting the fusion process. Many of the studies of the fusion of biological membranes have been done with the fusion of enveloped viruses with other membranes. One reason for this is that the number of proteins involved in viral fusion is relatively simple, often requiring only a single protein. For many enveloped viruses, the structure of their fusion proteins has certain common elements, suggesting that they all promote fusion by an analogous mechanism. Some aspects of this mechanism also appears to be common to intracellular fusion, although several proteins are involved in that process which is more complex and regulated than is viral fusion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.015 |
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".