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Record W4412727004 · doi:10.1021/acs.jcim.5c01063

Recent Developments in Amber Biomolecular Simulations

2025· article· en· W4412727004 on OpenAlexaff
David A. Case, David S. Cerutti, Vinícius Wilian D. Cruzeiro, Thomas A. Darden, Robert E. Duke, Mahdieh Ghazimirsaeed, George M. Giambaşu, Timothy J. Giese, Andreas Goetz, Robert C. Harris, Koushik Kasavajhala, Tai‐Sung Lee, Zhen Li, Charles Y. Lin, Jian Liu, Yinglong Miao, Romelia Salomon-Ferrrer, Jana Shen, Ryan Snyder, Jason Swails, Ross C. Walker, Jinan Wang, Xiongwu Wu, Jinzhe Zeng, Thomas E. Cheatham, Daniel R. Roe, Adrián E. Roitberg, Carlos Simmerling, Darrin M. York, Maria C. Nagan, Kenneth M. Merz

Bibliographic record

VenueJournal of Chemical Information and Modeling · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsAdvanced Micro Devices (Canada)
FundersDivision of ChemistryOffice of Advanced CyberinfrastructureNational Heart, Lung, and Blood InstituteNational Institute of General Medical SciencesNational Science Fund for Distinguished Young ScholarsNational Institutes of HealthAdvanced Micro DevicesIntel Corporation
KeywordsReplicaComputer scienceGraphicsSoftwareGraphics processing unitComputational scienceInterface (matter)Software packageMessage Passing InterfaceMolecular dynamicsParallel computingComputer graphics (images)Message passingOperating systemChemistryComputational chemistry

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Amber is a molecular dynamics (MD) software package first conceived by Peter Kollman, his lab and collaborators to simulate biomolecular systems. The pmemd module is available as a serial version for central processing units (CPUs), NVIDIA and Advanced Micro Devices (AMD) graphics processing unit (GPU) versions as well as Message Passing Interface (MPI) parallel versions. Advanced capabilities include thermodynamic integration, replica exchange MD and accelerated MD methods. A brief update to the software and recently added capabilities is described in this Application Note.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.006

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 head0.010
GPT teacher head0.275
Teacher spread0.266 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreReview

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".

Quick stats

Citations114
Published2025
Admission routes1
Has abstractyes

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