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Data & Code for Using Artificial Intelligence to Predict the Financial Impact of Climate Transition Risks Within Organisations

<p>This repository contains the code used for the article</p> <p>"P&eacute;rez-P&eacute;rez, Juan F.,&nbsp;Bonet,&nbsp;Isis,&nbsp;S&aacute;nchez-Pinz&oacute;n,&nbsp;Mar&iacute;a Solange,&nbsp;Caraffini,&nbsp;Fabio,&nbsp;Lochmuller,&nbsp;Christian,&nbsp;Using Artificial Intelligence to Predict the Financial Impact of Climate Transition Risks Within Organisations,&nbsp;<em>International Journal of Intelligent Systems</em>,&nbsp;2024, 3334263, 21 pages,&nbsp;2024.&nbsp;<a href="https://doi.org/10.1155/int/3334263">https://doi.org/10.1155/int/3334263</a>"</p> <p>&nbsp;including the code for generating data sets.&nbsp; Shall you use this code and data, please acknowledge the published article and this repository.</p>

ShareScore

24/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
0
Engagement
0

Dataset details

Repository
zenodo
Published
April 17, 2024
License
cc-by-4.0
DOI
10.5281/zenodo.10991562

Scored with release 0.9.0

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