Correction: Using machine learning to understand age and gender classification based on infant temperament von Gartstein, Maria A, Seamon, D Erich, Mattera, Jennifer A, Enlow, Michelle Bosquet, Wright, Rosalind J, Perez-Edgar, Koraly, Buss, Kristin A, LoBue, Vanessa, Bell, Martha Ann, Goodman, Sherryl H, Spieker, Susan, Bridgett, David J, Salisbury, Amy L, Gunnar, Megan R, Mliner, Shanna B, Muzik, Maria, Stifter, Cynthia A, Planalp, Elizabeth M, Mehr, Samuel A, Spelke, Elizabeth S, Lukowski, Angela F, Groh, Ashley M, Lickenbrock, Diane M, Santelli, Rebecca, Schudlich, Tina Du Rocher, Anzman-Frasca, Stephanie, Thrasher, Catherine, Diaz, Anjolii, Dayton, Carolyn, Moding, Kameron J, Jordan, Evan M

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Using machine learning to understand age and gender classification based on infant temperament von 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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Using machine learning to understand age and gender classification based on infant temperament von Gartstein, Maria A, Seamon, D. Erich, Mattera, Jennifer A, Bosquet Enlow, Michelle, Wright, Rosalind J, Perez-Edgar, Koraly, Buss, Kristin A, LoBue, Vanessa, Bell, Martha Ann, Goodman, Sherryl H, Spieker, Susan, Bridgett, David J, Salisbury, Amy L, Gunnar, Megan R, Mliner, Shanna B, Muzik, Maria, Stifter, Cynthia A, Planalp, Elizabeth M, Mehr, Samuel A, Spelke, Elizabeth S, Lukowski, Angela F, Groh, Ashley M, Lickenbrock, Diane M, Santelli, Rebecca, Du Rocher Schudlich, Tina, Anzman-Frasca, Stephanie, Thrasher, Catherine, Diaz, Anjolii, Dayton, Carolyn, Moding, Kameron J, Jordan, Evan M

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A GIS Model to Calculate Sediment Yields from a Small Rural Watershed, Old Woman Creek, Erie and Huron Counties, Ohio von Evans, James E, Seamon, DErich

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Do Invasive and Naturalized Aphid Pest Populations Respond Differently to Climatic and Landscape Factors? von Adhikari, Subodh, Seamon, Erich, Wu, Ying, Sadeghi, Seyed E., Eigenbrode, Sanford D.

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Latent Profile and Cluster Analysis of Infant Temperament: Comparisons Across Person-Centered Approaches von Gartstein, Maria A., Prokasky, Amanda, Bell, Martha Ann, Calkins, Susan, Bridgett, David J., Braungart-Rieker, Julia, Leerkes, Esther, Cheatham, Carol L., Eiden, Rina D., Mize, Krystal D., Jones, Nancy Aaron, Mireault, Gina, Seamon, Erich

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Using machine learning to understand age and gender classification based on infant temperament von Gartstein, Maria A, Seamon, D Erich, Mattera, Jennifer A, Bosquet Enlow, Michelle, Wright, Rosalind J, Perez-Edgar, Koraly, Buss, Kristin A, LoBue, Vanessa, Bell, Martha Ann, Goodman, Sherryl H, Spieker, Susan, Bridgett, David J, Salisbury, Amy L, Gunnar, Megan R, Mliner, Shanna B, Muzik, Maria, Stifter, Cynthia A, Planalp, Elizabeth M, Mehr, Samuel A, Spelke, Elizabeth S, Lukowski, Angela F, Groh, Ashley M, Lickenbrock, Diane M, Santelli, Rebecca, Du Rocher Schudlich, Tina, Anzman-Frasca, Stephanie, Thrasher, Catherine, Diaz, Anjolii, Dayton, Carolyn, Moding, Kameron J, Jordan, Evan M

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