<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Peijin Li</style></author><author><style face="normal" font="default" size="100%">Rongqi Zhu</style></author><author><style face="normal" font="default" size="100%">McJeon, Haewon</style></author><author><style face="normal" font="default" size="100%">Byers, Edward</style></author><author><style face="normal" font="default" size="100%">Peijie Zhou</style></author><author><style face="normal" font="default" size="100%">Ou, Yang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using deep learning to generate key variables in global mitigation scenarios</style></title><secondary-title><style face="normal" font="default" size="100%">Nature Climate Change</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2025</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.nature.com/articles/s41558-025-02352-8</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">15</style></volume><pages><style face="normal" font="default" size="100%">760–768</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>