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Perspective on the Martini model

2013· review· en· 1,215 citations· W2081724315 on OpenAlex· 10.1039/c3cs60093a

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

Classifier prediction

metacan-v1-d91a1de5be90

Predictions imitate two machine teachers. Scores are not calibrated prevalence probabilities.

Classifier candidate
Theoretical or conceptualNot applicable
Classifier consensus
Theoretical or conceptual
Teacher imitation scores

Codex

Theoretical or conceptual0.144
Other design0.106
Not applicable0.018
Simulation or modelling0.003
Systematic review0.001
Bench or experimental0.001
Metaresearch0.000
Open science0.000
Meta-epidemiology (broad)0.000
Qualitative0.000
Meta-epidemiology (narrow)0.000
Scholarly communication0.000
Science and technology studies0.000
Meta-analysis0.000
Research integrity0.000
Bibliometrics0.000
Randomized trial0.000
Non-randomized trial0.000
Observational0.000
Case report0.000

Gemma

Not applicable0.476
Theoretical or conceptual0.035
Simulation or modelling0.014
Bench or experimental0.001
Open science0.001
Meta-epidemiology (broad)0.000
Qualitative0.000
Metaresearch0.000
Research integrity0.000
Systematic review0.000
Science and technology studies0.000
Meta-analysis0.000
Meta-epidemiology (narrow)0.000
Bibliometrics0.000
Scholarly communication0.000
Case report0.000
Randomized trial0.000
Non-randomized trial0.000
Observational0.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.046
GPT teacher head0.333
Teacher spread
0.287 how far apart the two teachers sit on this one work
Validation status
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

Abstract

The Martini model, a coarse-grained force field for biomolecular simulations, has found a broad range of applications since its release a decade ago. Based on a building block principle, the model combines speed and versatility while maintaining chemical specificity. Here we review the current state of the model. We describe recent highlights as well as shortcomings, and our ideas on the further development of the model.

Retrieved from PubMed through NCBI EFetch. Structured section labels are preserved.