Evidence map›Paper›PMID 41515370›Full record

ArticleMolecules (Basel, Switzerland)2025

Conditional Variational AutoEncoder to Predict Suitable Conditions for Hydrogenation Reactions.

Daniyar Mazitov, Timur Gimadiev, Assima Poyezzhayeva, Valentina Afonina, Timur Madzhidov

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

5 authors.

Daniyar MazitovA.M. Butlerov Institute of Chemistry, Kazan Federal University, Kremlevskaya Str. 18, 420008 Kazan, Russia.ORCID 0000-0003-1305-4377
Timur GimadievA.M. Butlerov Institute of Chemistry, Kazan Federal University, Kremlevskaya Str. 18, 420008 Kazan, Russia.ORCID 0000-0001-5012-0308
Assima PoyezzhayevaA.M. Butlerov Institute of Chemistry, Kazan Federal University, Kremlevskaya Str. 18, 420008 Kazan, Russia.ORCID 0000-0002-6820-6385
Valentina AfoninaA.M. Butlerov Institute of Chemistry, Kazan Federal University, Kremlevskaya Str. 18, 420008 Kazan, Russia.ORCID 0000-0002-5291-8636
Timur MadzhidovChemistry Solutions, Elsevier, London EC2Y 5AS, UK.ORCID 0000-0002-3834-6985

Funding

The government assignment for FRC Kazan Scientific Center of RAS 125030503189-7
6 · The paper itself

Abstract

Reaction conditions (RCs) are a crucial part of reaction definition, and their accurate prediction is an important component of chemical synthesis planning. The existence of multiple combinations of RCs capable of achieving the desired result complicates the task of condition recommendation. Herein, we propose a conditional variational autoencoder (CVAE) generative model to predict suitable RCs. The CVAE model has been customized to generate diverse sets of valid conditions, ensuring high flexibility and accuracy, while circumventing the necessity for enumeration or combinatorial search of potential RCs. The efficacy of the CVAE approaches was evaluated using hydrogenation reactions and other H

Indexed as

condensed graph of reactionconditional variational autoencoderH2-mediated reactionshydrogenation reactionshydrogenolysisreaction condition prediction

Identifiers

PMID41515370
PMCPMC12786955

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.