Equilibrium dynamics of single DNA molecules confined to nanopit structures
Bibliographic record
Abstract
Introduction: of great interest in the physical sciences today, is the study of single molecules in nano-fluidic devices. These ‘labs-on-a-chip’ can provide the basic framework for quantifying the behavior of molecules, such as polymers, under confinement. This study is an investigation of a theoretical free-energy model used to predict thermodynamic properties of DNA molecules situated in a device called a nanopit array. Two parameters in the model, molecule length and nanopit width, are varied and tested against experimental data. Methods: Video-fluorescence microscopy was used to image single DNA molecules in the nanopit array; analysis consisted of determining the average number of nanopits occupied by a single DNA molecule over time. results: good qualitative agreement was reached between theory and experiment for the nanopit width variation, but molecule-length variation predictions were shown to still need improvement. A least-squares fit of the theory to the data suggested that the entropic parameter, A, and the excluded volume term, b, have a modified dependence on nanoslit height and nanopit depth than what is currently predicted by the model. discussion: These experiments confirm that the theoretical model is adequate under certain regimes and predicts conditions under which theory and experiment may significantly diverge. Modifications to the theory are proposed.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".