Evidence map›Paper›PMID 38816859›Full record

ArticleJournal of cheminformatics2024

Identifying uncertainty in physical-chemical property estimation with IFSQSAR.

Trevor N Brown, Alessandro Sangion, Jon A Arnot

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

3 authors.

Trevor N BrownARC Arnot Research & Consulting, Toronto, ON, M4C 2B4, Canada. trevor.n.brown@gmail.com.
Alessandro SangionARC Arnot Research & Consulting, Toronto, ON, M4C 2B4, Canada.
Jon A ArnotARC Arnot Research & Consulting, Toronto, ON, M4C 2B4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study describes the development and evaluation of six new models for predicting physical-chemical (PC) properties that are highly relevant for chemical hazard, exposure, and risk estimation: solubility (in water S

Indexed as

Abraham solvation modelApplicability domainChemical propertiesHenry’s Law constantOctanol–water partitioningPPLFERPrediction uncertaintyQSPRSolubilityVapor pressure

Identifiers

PMID38816859
PMCPMC11140865

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.