Evidence map›Paper›PMID 38115916›Full record

ArticleJournal of chemical and engineering data2023

Lessons Learned from Multiobjective Automatic Optimizations of Classical Three-Site Rigid Water Models Using Microscopic and Macroscopic Target Experimental Observables.

Mattia Perrone, Riccardo Capelli, Charly Empereur-Mot, Ali Hassanali, Giovanni M Pavan

Abstract read
In one paragraph

Article in Journal of chemical and engineering data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Building Water Models Compatible with Charge Scaling Molecular Dynamics.The journal of physical chemistry letters · 2024
    Article
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

5 authors.

Mattia PerroneDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino I-10129, Italy.
Riccardo CapelliDepartment of Biosciences, Università degli Studi di Milano, Via Celoria 26, Milano I-20133, Italy.ORCID https://orcid.org/0000-0001-9522-3132
Charly Empereur-MotDepartment of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Polo Universitario Lugano, Campus Est, Via la Santa 1, Lugano-Viganello CH-6962, Switzerland.ORCID https://orcid.org/0000-0001-6972-8225
Ali HassanaliThe Abdus Salam International Center for Theoretical Physics, Strada Costiera 11, Trieste 34151, Italy.ORCID https://orcid.org/0000-0002-3208-1488
Giovanni M PavanDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino I-10129, Italy.ORCID https://orcid.org/0000-0002-3473-8471

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of accurate water models is of primary importance for molecular simulations. Despite their intrinsic approximations, three-site rigid water models are still ubiquitously used to simulate a variety of molecular systems. Automatic optimization approaches have been recently used to iteratively refine three-site water models to fit macroscopic (average) thermodynamic properties, providing state-of-the-art three-site models that still present some deviations from the liquid water properties. Here, we show the results obtained by automatically optimizing three-site rigid water models to fit a combination of microscopic and macroscopic experimental observables. We use

Identifiers

PMID38115916
PMCPMC10726314

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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.