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Record W2013926038 · doi:10.1088/1478-3975/7/3/036001

Coarse-graining RNA nanostructures for molecular dynamics simulations

2010· article· en· W2013926038 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysical Biology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsWilfrid Laurier UniversityWestern University
FundersNational Institutes of Health
KeywordsRNAContext (archaeology)Molecular dynamicsGranularityNucleotideNanobiotechnologyBiological systemStatistical physicsPhysicsComputational biologyChemistryComputer scienceNanotechnologyBiologyMaterials scienceComputational chemistryBiochemistry

Abstract

fetched live from OpenAlex

A series of coarse-grained models have been developed for study of the molecular dynamics of RNA nanostructures. The models in the series have one to three beads per nucleotide and include different amounts of detailed structural information. Such a treatment allows us to reach, for systems of thousands of nucleotides, a time scale of microseconds (i.e. by three orders of magnitude longer than in full atomistic modeling) and thus to enable simulations of large RNA polymers in the context of bionanotechnology. We find that the three-beads-per-nucleotide models, described by a set of just a few universal parameters, are able to describe different RNA conformations and are comparable in structural precision to the models where detailed values of the backbone P-C4' dihedrals taken from a reference structure are included. These findings are discussed in the context of RNA conformation classes.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.281
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it