dc.contributor.author
Christmann, Mathias
dc.date.accessioned
2025-01-10T11:50:11Z
dc.date.available
2025-01-10T11:50:11Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/46177
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-45888
dc.description.abstract
A Python script for the systematic, high-throughput analysis of accurate mass data was developed and tested on more than 3000 Supporting Information (SI) PDFs from Organic Letters. For each SI file, quadruplets of molecular formula, measured ion, e.g., [M + Na]+, and reported calculated and found masses were extracted and analyzed. Interestingly, only 40% of the files containing readable accurate mass data were both internally consistent and in compliance with The ACS Guide to Scholarly Communication. The analysis revealed unexpected errors and provided actionable advice on how to improve data quality.
en
dc.format.extent
4 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
Chemical calculations
en
dc.subject
Quality management
en
dc.subject.ddc
500 Naturwissenschaften und Mathematik::540 Chemie::540 Chemie und zugeordnete Wissenschaften
dc.title
What I Learned from Analyzing Accurate Mass Data of 3000 Supporting Information Files
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.doi
10.1021/acs.orglett.4c03458
dcterms.bibliographicCitation.journaltitle
Organic Letters
dcterms.bibliographicCitation.number
1
dcterms.bibliographicCitation.pagestart
4
dcterms.bibliographicCitation.pageend
7
dcterms.bibliographicCitation.volume
27
dcterms.bibliographicCitation.url
https://doi.org/10.1021/acs.orglett.4c03458
refubium.affiliation
Biologie, Chemie, Pharmazie
refubium.affiliation.other
Institut für Chemie und Biochemie

refubium.funding
ACS Publications
refubium.note.author
Die Publikation wurde aus Open Access Publikationsgeldern der Freien Universität Berlin gefördert.
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
1523-7052