New fix

HEPML.bib

@@ -10388,13 +10388,13 @@ @article{LeBlanc:2022bwd
 }
 
 %June 20, 2022
-@inbook{Coadou:2022nsh,
+@article{Coadou:2022nsh,
     author = "Coadou, Yann",
     title = "{Boosted decision trees}",
     eprint = "2206.09645",
     journal="Artificial Intelligence for High Energy Physics",
     pages="9",
-    doi="10.1142/9789811234033\_0002",
+    doi="10.1142/9789811234033_0002",
     journal="Artificial Intelligence for High Energy Physics",
     pages="9",
     archivePrefix = "arXiv",

README.md

@@ -49,7 +49,7 @@ This review was built with the help of the HEP-ML community, the [INSPIRE REST A
 * [New directions for surrogate models and differentiable programming for High Energy Physics detector simulation](https://arxiv.org/abs/2203.08806)
 * [Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges](https://arxiv.org/abs/2203.12852)
 * [Physics Community Needs, Tools, and Resources for Machine Learning](https://arxiv.org/abs/2203.16255)
-* [Boosted decision trees](https://arxiv.org/abs/2206.09645) [[DOI](https://doi.org/10.1142/9789811234033\_0002)]
+* [Boosted decision trees](https://arxiv.org/abs/2206.09645) [[DOI](https://doi.org/10.1142/9789811234033_0002)]
 * [Data Science and Machine Learning in Education](https://arxiv.org/abs/2207.09060)
 * [Interpretable Uncertainty Quantification in AI for HEP](https://arxiv.org/abs/2208.03284) [[DOI](https://doi.org/10.2172/1886020)]
 * [Modern Machine Learning for LHC Physicists](https://arxiv.org/abs/2211.01421)

docs/index.md

@@ -80,7 +80,7 @@ const expandElements = shouldExpand => {
     * [New directions for surrogate models and differentiable programming for High Energy Physics detector simulation](https://arxiv.org/abs/2203.08806)
     * [Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges](https://arxiv.org/abs/2203.12852)
     * [Physics Community Needs, Tools, and Resources for Machine Learning](https://arxiv.org/abs/2203.16255)
-    * [Boosted decision trees](https://arxiv.org/abs/2206.09645) [[DOI](https://doi.org/10.1142/9789811234033\_0002)]
+    * [Boosted decision trees](https://arxiv.org/abs/2206.09645) [[DOI](https://doi.org/10.1142/9789811234033_0002)]
     * [Data Science and Machine Learning in Education](https://arxiv.org/abs/2207.09060)
     * [Interpretable Uncertainty Quantification in AI for HEP](https://arxiv.org/abs/2208.03284) [[DOI](https://doi.org/10.2172/1886020)]
     * [Modern Machine Learning for LHC Physicists](https://arxiv.org/abs/2211.01421)