Bibliographic record
Abstract
With advancements of modern biophysical tools and superresolution imaging, cell biology is entering a new phase of research with technological power fitting for membrane dynamics analyses. However, our current knowledge base of cellular signaling events is mostly built on a network of protein interactions, which is incompatible with the essential roles of membrane activities in those events. The lack of a theoretical platform is rendering biophysical analyses of membrane biology supplementary to the protein-centric paradigm. We hypothesize a framework of signaling events mediated by lipid dynamics and argue that this is the evolutionarily obligatory developmental path of cellular complexity buildup. In this framework, receptors are the late comers, integrating into the pre-existing membrane based signaling events using their lipid interface as the point of entry. We further suggest that the reason for cell surface receptors to remain silent at the resting state is via the suppression effects of their surrounding lipids. The avoidance of such a suppression, via ligand binding or lipid domain disruption, enables the receptors to autonomously integrate themselves into the preexisting networks of signaling cascades.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".