Evidence map›Paper›PMID 40572558›Full record

ArticleMolecules (Basel, Switzerland)2025

Gaussian Process Regression for Mapping Free EnergyLandscape of Mg

Wasut Pornpatcharapong

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Wasut PornpatcharapongDepartment of Chemistry, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand.ORCID 0000-0002-8834-8428

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Free energy landscapes are pivotal for understanding molecular interactions in solution, yet their reconstruction in complex systems remains computationally demanding. In this study, we integrated Gaussian process regression (GPR) with well-tempered metadynamics (WT-MTD) to efficiently map the free energy landscape of the Mg

Indexed as

enhanced samplingfree energyGPRion pairingmachine learningmetadynamicsmolecular dynamicssolvation

Identifiers

PMID40572558
PMCPMC12196332

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.