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Author Correction: Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284833/ https://www.ncbi.nlm.nih.gov/pubmed/37344520 http://dx.doi.org/10.1038/s41598-023-36579-2 |
| _version_ | 1785061478300123136 |
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| author | Matz, Sandra C. Bukow, Christina S. Peters, Heinrich Deacons, Christine Dinu, Alice Stachl, Clemens |
| author_facet | Matz, Sandra C. Bukow, Christina S. Peters, Heinrich Deacons, Christine Dinu, Alice Stachl, Clemens |
| author_sort | Matz, Sandra C. |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-10284833 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2023 |
| publisher | Nature Publishing Group UK |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-102848332023-06-23 Author Correction: Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics Matz, Sandra C. Bukow, Christina S. Peters, Heinrich Deacons, Christine Dinu, Alice Stachl, Clemens Sci Rep Author Correction Nature Publishing Group UK 2023-06-21 /pmc/articles/PMC10284833/ /pubmed/37344520 http://dx.doi.org/10.1038/s41598-023-36579-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
| spellingShingle | Author Correction Matz, Sandra C. Bukow, Christina S. Peters, Heinrich Deacons, Christine Dinu, Alice Stachl, Clemens Author Correction: Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics |
| title | Author Correction: Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics |
| title_full | Author Correction: Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics |
| title_fullStr | Author Correction: Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics |
| title_full_unstemmed | Author Correction: Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics |
| title_short | Author Correction: Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics |
| title_sort | author correction: using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics |
| topic | Author Correction |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284833/ https://www.ncbi.nlm.nih.gov/pubmed/37344520 http://dx.doi.org/10.1038/s41598-023-36579-2 |
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