Integrated Database of Force-Field Parameters, Experimental Measurements and Molecular Dynamics Simulations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Molecular Dynamic (MD) simulation is a vital theoretical tool for exploring nucleic acids (RNA, DNA), proteins and other (bio)molecular systems, generating vast amounts of data daily. Efficient storage and possible reuse of this data is a persistent challenge. Here, we introduce IDA (Integrated DAtabase of force fields and datasets from experiments and MD simulations), an innovative database scheme for datasets from various types of MD simulations. IDA supports outputs from different MD approaches, i.e., standard MD simulations, importance sampling techniques, simulated annealing, and other enhanced sampling methods including replica-exchange simulations. IDA also houses a collection of molecule-specific force fields (FFs) and experimental datasets. Uploaded MD outputs, FFs, and experimental data are integrated in a standardized format, allowing efficient data mining and extraction of valuable insights from the extensive data generated by diverse MD simulations. With the data and metadata holdings of IDA, and the prospective assignment of persistent identifiers, our work aims to make key steps towards making MD data FAIR (findable, accessible, interoperable, reusable).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it