The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Machine learning for predicting soil classes in three semi-arid landscapes
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Citations
Cites
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
Gene selection for cancer classification using support vector machines
Guyon, I., Weston, J., Barnhill, S., & Vapnik, V. (2002) · Machine Learning · doi:10.1023/a:1012487302797 · Cited by 9,954
Kuhn, M., & Johnson, K. (2013) · doi:10.1007/978-1-4614-6849-3 · Cited by 6,788 · cited 4×
“4 Covariate selection 289 290 Recursive feature elimination (Guyon et al., 2002; Kuhn and Johnson, 2013) was used to identify 291 an optimal subset of covariates from the set of all available covariates (covariate set 1+2) for each area 292 (Fig.”
MethodInfluentialVerification of forecasts expressed in terms of probability
BRIER, G. W. (1950) · Monthly Weather Review · doi:10.1175/1520-0493(1950)078%3c0001:vofeit%3e2.0.co;2 · cited 2×
“…distance to roads was included for another 364 purpose not thought to be related to soil taxonomic classes (impact of disturbance on vegetation) in the 365 initial cLHS. 366 367 2.5 Model accuracy comparison 368 369 Kappa analysis and Brier scores (Brier, 1950) were used to compare model accuracy.”
MethodInfluential
Cited by
Meyer, H., Reudenbach, C., Wöllauer, S., & Nauss, T. (2019) · Ecological Modelling · doi:10.1016/j.ecolmodel.2019.108815 · Cited by 509
Modelling and mapping soil organic carbon stocks in Brazil
Gomes, L. C., Faria, R. M., de Souza, E., Veloso, G. V., Schaefer, C. E. G. R., & Filho, E. I. F. (2019) · Geoderma · doi:10.1016/j.geoderma.2019.01.007 · Cited by 470
Condran, S., Bewong, M., Islam, M. Z., Maphosa, L., & Zheng, L. (2022) · IEEE Access · doi:10.1109/access.2022.3188649 · Cited by 99
Metadata
- Authors
- Brungard, C. W., Boettinger, J. L., Duniway, M. C., Wills, S. A., & Edwards, T. C.
- Venue
- Geoderma
- Publisher
- Elsevier BV
- Published
- 2015-02
- Volume
- 239-240
- Pages
- 68-83
- ISSN
- 0016-7061 (ISSN-L)
- OpenAlex
- W2089097786
- Cited by
- 395
- References
- 4
- FWCI
- 9.33
- 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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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.
