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

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

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Age and gender differences are prominent in the temperament literature, with the former particularly salient in infancy and the latter noted as early as the first year of life. This study represents a meta-analysis utilizing Infant Behavior Questionnaire-Revised (IBQ-R) data collected across multipl...

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Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2022-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0266026

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https://doi.org/10.1371/journal.pone.0266026

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