The DOI matches its Crossref record.
Principal components analysis (PCA)
Overview
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Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
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Citations
Cited by
Deep learning in cancer diagnosis, prognosis and treatment selection
Tran, K. A., Kondrashova, O., Bradley, A., Williams, E. D., Pearson, J. V., & Waddell, N. (2021) · Genome Medicine · doi:10.1186/s13073-021-00968-x · Cited by 932
Detecting Fake Accounts on Social Media
Khaled, S., El-Tazi, N., & Mokhtar, H. M. O. (2018) · 2018 IEEE International Conference on Big Data (Big Data) · doi:10.1109/bigdata.2018.8621913 · Cited by 131
When deep learning meets edge computing
Huang, Y., Ma, X., Fan, X., Liu, J., & Gong, W. (2017) · 2017 IEEE 25th International Conference on Network Protocols (ICNP) · doi:10.1109/icnp.2017.8117585 · Cited by 89
Cundari, T. R., Sârbu, C., & Pop, H. F. (2002) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci025524s · Cited by 53
Predicting clinical responses in major depression using intrinsic functional connectivity
Qin, J., Shen, H., Zeng, L.-L., Jiang, W., Liu, L., & Hu, D. (2015) · NeuroReport · doi:10.1097/wnr.0000000000000407 · Cited by 43
Metadata
- Authors
- Maćkiewicz, A., & Ratajczak, W.
- Venue
- Computers & Geosciences
- Publisher
- Elsevier BV
- Published
- 1993-03
- Volume
- 19
- Issue
- 3
- Pages
- 303-342
- ISSN
- 0098-3004 (ISSN-L)
- OpenAlex
- W2027461913
- Cited by
- 1,734
- References
- 0
- FWCI
- 0.93
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Principal components analysis (PCA). https://app.cochat.ai/papers/10.1016/0098-3004(93)90090-r
- The paper
- Maćkiewicz, A., & Ratajczak, W. (1993). Principal components analysis (PCA). Computers & Geosciences. https://doi.org/10.1016/0098-3004(93)90090-r
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
