Skip to content
Descubridor Institucional UMAR
Inicio
Búsqueda avanzada
Explorar
Inicio
Búsqueda avanzada
Explorar
Login
Language
English
Deutsch
Español
Français
Italiano
All Fields
Title
Author
Subject
Call Number
ISBN/ISSN
Tag
Find
Advanced
Leveraging unsupervised machine learning to examine women's vulnerability to climate change
Leveraging unsupervised machine learning to examine women's vulnerability to climate change
Fuente:
Wiley Open Access
Saved in:
Bibliographic Details
Main Authors:
German Caruso
,
Valerie Mueller
,
Alexis Villacis
Format:
Artículo Open Access
Published:
Wiley
2024
Subjects:
Applied Economic Perspectives and Policy
Online Access:
Acceder al recurso
Tags:
Add Tag
No Tags, Be the first to tag this record!
Cite this
Text this
Email this
Print
Export Record
Export to RefWorks
Export to EndNoteWeb
Export to EndNote
Save to List
Permanent link
Holdings
Description
Comments
Similar Items
Staff View
Internet
https://onlinelibrary.wiley.com/doi/10.1002/aepp.13444
Similar Items
A machine learning‐based exploration of resilience and food security
by: Alexis H. Villacis, et al.
Published: (2024)
Public agricultural research, political economy, and climate change: A literature review
by: Ruiqing Miao, et al.
Published: (2024)
Using machine‐learning methods in meta‐analyses: An empirical application on consumer acceptance of meat alternatives
by: Jiayu Sun, et al.
Published: (2024)
Do Zambian farmers manage climate risks?
by: Soyoka Okamura, et al.
Published: (2025)
How did consumers change their grocery spending in response to changes in Supplemental Nutrition Assistance Program benefit generosity?
by: Kassandra Martinchek, et al.
Published: (2025)