Statistical Analysis of the Effect of Simulation Time on the Results of Molecular Dynamics Studies of Food Proteins: A Study of the Ara h 6 Peanut Protein
Bibliographic record
Abstract
GROMACS MD simulations of food proteins and processes are often run over relatively short simulation lengths due to their high computational power demand. As long-timescale simulations are not always feasible, the purpose of this study was to determine, statistically, how simulation time affects conclusions drawn from GROMACS MD studies of food proteins. The Ara h 6 peanut allergen, undergoing heat processing at 300 K, 350 K, 400 K and 450 K, was used as the model in this study, and 2 ns, 20 ns and 200 ns GROMACS MD simulation lengths were investigated. The statistical analysis performed, using both one-way and two-way ANOVA tests, suggested that, depending on the selected simulation length, different final conclusions may be drawn regarding the effect that thermal processing temperature has on the geometric features of the Ara h 6 allergen. This was observed for many of the geometric features used to characterize the Ara h 6 allergen in this study, including RMSD, Rg, total number of intra-peptide hydrogen bonds and SASA. An inadequate sample size was, however, identified as a major limitation in this study.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".