Free-energy measuring nanopore device
Bibliographic record
Abstract
Free energies (FEs) in molecular sciences can be used to quantify the stability of folded molecules. In this article, we introduce nanopores for measuring FEs. We pull DNA hairpin-forming molecules through a nanopore, measure work, and estimate the FE change in the slow limit, and with the Jarzynski fluctuation theorem (FT) at fast pulling times. We also pull our molecule with optical tweezers, compare it to nanopores, and explore how sampling single molecules from equilibrium or a folded ensemble affects the FE estimate via the FT. The nanopore experiment helps us address and overcome the conceptual problem of equilibrium sampling in single-molecule pulling experiments. Only when molecules are sampled from an equilibrium ensemble do nanopore and tweezer FE estimates mutually agree. We demonstrate that nanopores are very useful tools for comparing FEs of two molecules at finite times and we propose future applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".