Bibliographic record
Abstract
Rupturing fluid membrane vesicles with a steady ramp of micropipette suction yields a tension distribution that images the kinetic process of membrane failure. When plotted on a log scale of tension loading rate, the distribution peaks (membrane strengths) define a dynamic tension spectrum with distinct regimes that reflect passage of prominent energy barriers along the pathway to rupture. Demonstrated here by tests on giant PC lipid vesicles over loading rates from 0.06–60 mN/m/s, the stochastic process of rupture can be modelled as a causal sequence of two thermally-activated transitions where each transition governs membrane strength on separate scales of loading rate. Under fast ramps of tension, a steep linear regime appears in each spectrum at high strengths which implies that failure requires nucleation of a rare nanoscale defect. The slope and projected intercept yield defect size and spontaneous production rate respectively. However, under slow ramps of loading, the spectrum crosses over to a shallow-curved regime at lower strength, which is consistent with the kinetic impedance to opening an unstable hole in a fluid film. The dependence of rupture tension on rate reveals hole edge energy and frequency scale for thermal fluctuations in size.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".