Evidence map›Paper›PMID 38009856›Full record

ArticleJournal of chemical theory and computation2023

Evolutionary Monte Carlo of QM Properties in Chemical Space: Electrolyte Design.

Konstantin Karandashev, Jan Weinreich, Stefan Heinen, Daniel Jose Arismendi Arrieta, Guido Falk von Rudorff, Kersti Hermansson, O Anatole von Lilienfeld

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of chemical theory and computation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Representative Random Sampling of Chemical Space.Journal of chemical theory and computation · 2025
    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

7 authors.

Konstantin KarandashevFaculty of Physics, University of Vienna, Kolingasse 14-16, AT-1090 Wien, Austria.ORCID 0000-0002-0943-3051
Jan WeinreichFaculty of Physics, University of Vienna, Kolingasse 14-16, AT-1090 Wien, Austria.ORCID 0000-0002-9332-4543
Stefan HeinenVector Institute for Artificial Intelligence, Toronto, M5S 1M1 Ontario, Canada.
Daniel Jose Arismendi ArrietaDepartment of Chemistry-Ångström Laboratory, Uppsala University, Box 538, SE-75121 Uppsala, Sweden.
Guido Falk von RudorffDepartment of Chemistry, University Kassel, Heinrich-Plett-Str.40, 34132 Kassel, Germany.ORCID 0000-0001-7987-4330
Kersti HermanssonDepartment of Chemistry-Ångström Laboratory, Uppsala University, Box 538, SE-75121 Uppsala, Sweden.
O Anatole von LilienfeldVector Institute for Artificial Intelligence, Toronto, M5S 1M1 Ontario, Canada.ORCID 0000-0001-7419-0466

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optimizing a target function over the space of organic molecules is an important problem appearing in many fields of applied science but also a very difficult one due to the vast number of possible molecular systems. We propose an evolutionary Monte Carlo algorithm for solving such problems which is capable of straightforwardly tuning both exploration and exploitation characteristics of an optimization procedure while retaining favorable properties of genetic algorithms. The method, dubbed MOSAiCS (

Identifiers

PMID38009856
PMCPMC10720348

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.