Evidence map›Paper›PMID 32226607›Full record

ArticleF1000Research2020

Machine learning meets pK

Marcel Baltruschat, Paul Czodrowski

Abstract read
In one paragraph

Article in F1000Research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Can Graph Neural Networks Understand Chemical Elements?Journal of chemical information and modeling · 2026
    Article
  3. Unifying pJournal of chemical information and modeling · 2026
    Article
  4. Benchmarking pJournal of chemical information and modeling · 2026
    Article
  5. Article
  6. Article
  7. Interpretable Deep-Learning pJournal of chemical information and modeling · 2025
    Article
  8. Article
  9. Article
  10. QupKake: Integrating Machine Learning and Quantum Chemistry for Micro-pJournal of chemical theory and computation · 2024
    Article
  11. Article
  12. Open-Source Machine Learning in Computational Chemistry.Journal of chemical information and modeling · 2023
    Review
  13. MF-SuP-pActa pharmaceutica Sinica. B · 2023
    Article
  14. Article
  15. Protein pJournal of chemical theory and computation · 2022
    Article
  16. Improving Small Molecule pKFrontiers in chemistry · 2022
    Article
  17. Overview of the SAMPL6 pKJournal of computer-aided molecular design · 2021
    Article
  18. Machine learning meets pKF1000Research · 2020
    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

2 authors.

Marcel BaltruschatFaculty of Chemistry and Chemical Biology, TU Dortmund University, Otto-Hahn-Strasse 6, 44227 Dortmund, Germany.ORCID 0000-0002-5230-487X
Paul CzodrowskiFaculty of Chemistry and Chemical Biology, TU Dortmund University, Otto-Hahn-Strasse 6, 44227 Dortmund, Germany.ORCID 0000-0002-7390-8795

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a small molecule pK

Indexed as

Machine LearningModels, ChemicalSoftwareKineticsdissociationmachine learningpKa valueprotonation

Identifiers

PMID32226607
PMCPMC7096188

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.