Progress in detection of and correction for low-energy contamination.

data quality metrics flawed standard uncertainties low-energy contamination robust metrics systematic errors

Journal

Journal of applied crystallography
ISSN: 0021-8898
Titre abrégé: J Appl Crystallogr
Pays: United States
ID NLM: 9876190

Informations de publication

Date de publication:
01 Aug 2023
Historique:
received: 10 01 2023
accepted: 30 05 2023
medline: 9 8 2023
pubmed: 9 8 2023
entrez: 9 8 2023
Statut: epublish

Résumé

Contamination with low-energy radiation leads to an increased number of weighted residuals being larger in absolute terms than three standard uncertainties. For a Gaussian distribution, these rare events occur only in 0.27% of all cases, which is a small number for small- to medium-sized data sets. The correct detection of rare events - and an adequate correction procedure - thus relies crucially on correct standard uncertainties, which are often not available [Henn (2019),

Identifiants

pubmed: 37555226
doi: 10.1107/S1600576723004764
pii: S1600576723004764
pmc: PMC10405589
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1200-1220

Informations de copyright

© Slawomir Domagala et al. 2023.

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Auteurs

Slawomir Domagala (S)

DataQ Intelligence, Fichtelgebirgsstrasse 66, 95448 Bayreuth, Germany.
Codivert, Żubrowa 15, 01-978 Warsaw, Poland.

Petrick Nourd (P)

DataQ Intelligence, Fichtelgebirgsstrasse 66, 95448 Bayreuth, Germany.

Kay Diederichs (K)

Department of Biology, University of Konstanz, Universitätsstrasse 19, 78457 Konstanz, Germany.

Julian Henn (J)

DataQ Intelligence, Fichtelgebirgsstrasse 66, 95448 Bayreuth, Germany.

Classifications MeSH