Evidence map›Paper›PMID 36434133›Full record

ArticleScientific reports2022

Precisely predicting the

Keunhong Jeong, Tae In Ryu, Seung-Ryul Hwang, Yoonjae Cho, Kyoung Chan Lim, Ung Hwi Yoon, Jin-Young Lee, Young Wook Yoon, Hey Jin Jeong

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Computation ofJournal of molecular modeling · 2025
    Article
  4. Review
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

9 authors.

Keunhong JeongDepartment of Physics and Chemistry, Korea Military Academy, Seoul, 01805, South Korea. doas1mind@kma.ac.kr.
Tae In RyuAccident Coordination and Training Division, National Institute of Chemical Safety (NICS), 90 Gajeongbuk-Ro, Yuseong-Gu, Daejeon, 34114, South Korea.
Seung-Ryul HwangAccident Coordination and Training Division, National Institute of Chemical Safety (NICS), 90 Gajeongbuk-Ro, Yuseong-Gu, Daejeon, 34114, South Korea.
Yoonjae ChoAccident Coordination and Training Division, National Institute of Chemical Safety (NICS), 90 Gajeongbuk-Ro, Yuseong-Gu, Daejeon, 34114, South Korea.
Kyoung Chan LimAgency for Defense Development (ADD), Yuseong-Gu, P.O. Box 35, Daejeon, 34186, South Korea.
Ung Hwi YoonDepartment of Physics and Chemistry, Korea Military Academy, Seoul, 01805, South Korea.
Jin-Young LeeAgency for Defense Development (ADD), Yuseong-Gu, P.O. Box 35, Daejeon, 34186, South Korea.
Young Wook YoonAccident Coordination and Training Division, National Institute of Chemical Safety (NICS), 90 Gajeongbuk-Ro, Yuseong-Gu, Daejeon, 34114, South Korea.
Hey Jin JeongDepartment of Physics and Chemistry, Korea Military Academy, Seoul, 01805, South Korea.

Funding

Agency for Defense Development 912709201
6 · The paper itself

Abstract

Following the recent terrorist attacks using Novichok agents and the subsequent decomposition operations, understanding the chemical structures of nerve agents has become important. To mitigate the ever-evolving threat of new variants, the Organization for the Prohibition of Chemical Weapons has updated the list of Schedule 1 substances defined by the Chemical Weapons Convention. However, owing to the several possible structures for each listed substance, obtaining an exhaustive dataset is almost impossible. Therefore, we propose a nuclear magnetic resonance-based prediction method for

Indexed as

Nerve AgentsMagnetic Resonance ImagingMagnetic Resonance SpectroscopyOrganophosphatesNerve AgentsnovichokOrganophosphates

Identifiers

PMID36434133
PMCPMC9700684

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.