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Open Access

Correction

Correction: Using machine learning to understand age and gender classification based on infant temperament

  • Maria A. Gartstein,
  • D. Erich Seamon,
  • Jennifer A. Mattera,
  • Michelle Bosquet Enlow,
  • Rosalind J. Wright,
  • Koraly Perez-Edgar,
  • Kristin A. Buss,
  • Vanessa LoBue,
  • Martha Ann Bell,
  • Sherryl H. Goodman,
  • Susan Spieker,
  • David J. Bridgett,
  • Amy L. Salisbury,
  • Megan R. Gunnar,
  • Shanna B. Mliner,
  • Maria Muzik,
  • Cynthia A. Stifter,
  • Elizabeth M. Planalp,
  • Samuel A. Mehr,
  • Elizabeth S. Spelke,
  • Angela F. Lukowski,
  • Ashley M. Groh,
  • Diane M. Lickenbrock,
  • Rebecca Santelli,
  • Tina Du Rocher Schudlich,
  • Stephanie Anzman-Frasca,
  • Catherine Thrasher,
  • Anjolii Diaz,
  • Carolyn Dayton,
  • Kameron J. Moding,
  •  [ ... ],
  • Evan M. Jordan
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The second author’s name is spelled incorrectly. The correct name is: Erich Seamon. The correct citation is: Gartstein MA, Seamon E, Mattera JA, Bosquet Enlow M, Wright RJ, Perez-Edgar K, et al. (2022) Using machine learning to understand age and gender classification based on infant temperament. PLOS ONE 17(4): e0266026. https://doi.org/10.1371/journal.pone.0266026

There is an error in affiliation 2 for author Erich Seamon. The correct affiliation 2 is: Institute for Modeling, Collaboration, and Innovation, University of Idaho, Moscow, Idaho, USA.

Reference

  1. 1. Gartstein MA, Seamon DE, Mattera JA, Bosquet Enlow M, Wright RJ, Perez-Edgar K, et al. (2022) Using machine learning to understand age and gender classification based on infant temperament. PLOS ONE 17(4): e0266026. https://doi.org/10.1371/journal.pone.0266026 pmid:35417495

Citation: Gartstein MA, Seamon DE, Mattera JA, Enlow MB, Wright RJ, Perez-Edgar K, et al. (2024) Correction: Using machine learning to understand age and gender classification based on infant temperament. PLoS ONE 19(12): e0316132. https://doi.org/10.1371/journal.pone.0316132

Published: December 17, 2024

Copyright: © 2024 Gartstein et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.