Contamination Artifacts
Contamination Artifacts is a type of artifact in data analysis and machine learning research that arises when extraneous, unintended, or spurious information inadvertently influences a dataset, model, or experimental outcome, thereby compromising the validity, generalizability, or interpretability of results due to the presence of such confounding elements.
11
Publications
535
Citations
38
Authors
15
Institutions
Publications per year
2017–2026
2
Parents
11
Morphine and codeine from mammalian brain.
Charles J. Weitz, Louise I. Lowney, Kym F. Faull et al. · Proceedings of the National Academy of Sciences · 1986 · 86 citations · Full text
Medicine, Neuroscience, Pharmacology +12
1–5 of 11
38
2
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 38
15
University of Utah
Salt Lake City, United States
2 h-index
10 publications
240 citations
Addiction Research Foundation
Birmingham, United States
1 h-index
3 publications
258 citations
Mersin Üniversitesi
Mersin, Türkiye
1 h-index
3 publications
33 citations
University of Copenhagen
Copenhagen, Denmark
1 h-index
2 publications
50 citations

Consejo Nacional de Investigaciones Científicas y Técnicas
Buenos Aires, Argentina
1 h-index
3 publications
108 citations
The University of Tokyo
Tokyo, Japan
1 h-index
1 publications
51 citations
National University of San Luis
San Luis, Argentina
1 h-index
3 publications
108 citations
Behavioral Pharma (United States)
La Jolla, United States
1 h-index
3 publications
258 citations
1–8 of 15
2 publications · 48 citations
2
h-index
1 publications · 146 citations
1
h-index
1 publications · 51 citations
1
h-index
PNAS · 1 publications · 86 citations
1
h-index
1 publications · 25 citations
1
h-index
1–5