机构

• 西北高原生物研究所 [48]
• 昆明植物研究所 [15]
• 心理研究所 [12]
• 大连化学物理研究所 [11]
• 地理科学与资源研究所 [6]
• 上海药物研究所 [4]
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采集方式

• OAI收割 [129]
• iSwitch采集 [4]

内容类型

• 期刊论文 [132]
• SCI/SSCI论文 [1]

发表日期

• 2023 [8]
• 2022 [9]
• 2021 [7]
• 2020 [4]
• 2019 [4]
• 2018 [4]
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学科主题

• Chemistry [3]
• Environmen... [3]
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浏览/检索结果: 共133条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择提交时间升序提交时间降序发表日期升序发表日期降序题名升序题名降序作者升序作者降序 Ecosystem responses dominate the trends of annual gross primary productivity over terrestrial ecosystems of China during 2000-2020 期刊论文  OAI收割 AGRICULTURAL AND FOREST METEOROLOGY, 2023, 卷号: 343, 页码: 109758 作者:  Zhu, Xian-Jin;  Yu, Gui-Rui;  Chen, Zhi;  Zhang, Wei-Kang;  Han, Lang   |  收藏  |  浏览/下载：13/0  |  提交时间：2023/12/04 Carbon cycles  Eddy covariance  Terrestrial ecosystems  Machine learning  Ecosystem responses   Evidence of palaeo-wildfire during the Early Cretaceous: macro-charcoal from the Chijinpu Formation (early Aptian) of northwestern China 期刊论文  OAI收割 HISTORICAL BIOLOGY, 2023, 页码: 12 作者:  Han, Lei;  Wu, Guang-Tao;  Sun, Bai-Nian   |  收藏  |  浏览/下载：7/0  |  提交时间：2023/10/24 Charcoal  palaeo-wildfire  gymnosperms  Early Cretaceous  Chijinpu Formation  northwestern China   A longitudinal resource for population neuroscience of school-age children and adolescents in China 期刊论文  OAI收割 SCIENTIFIC DATA, 2023, 卷号: 10, 期号: 1, 页码: 24 作者:  Fan, Xue-Ru;  Wang, Yin-Shan;  Chang, Da;  Yang, Ning;  Rong, Meng-Jie   |  收藏  |  浏览/下载：18/0  |  提交时间：2023/12/11 Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning 期刊论文  OAI收割 SCIENCE OF THE TOTAL ENVIRONMENT, 2023, 卷号: 857, 页码: 18 作者:  Zhu, Xian-Jin;  Yu, Gui-Rui;  Chen, Zhi;  Zhang, Wei-Kang;  Han, Lang   |  收藏  |  浏览/下载：41/0  |  提交时间：2022/12/09 Carbon cycle  Climate change  Eddy covariance  Terrestrial ecosystem  Machine learning  Scale extension   Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning 期刊论文  OAI收割 SCIENCE OF THE TOTAL ENVIRONMENT, 2023, 卷号: 857, 页码: 18 作者:  Zhu, Xian-Jin;  Yu, Gui-Rui;  Chen, Zhi;  Zhang, Wei-Kang;  Han, Lang   |  收藏  |  浏览/下载：28/0  |  提交时间：2022/12/09 Carbon cycle  Climate change  Eddy covariance  Terrestrial ecosystem  Machine learning  Scale extension   The Chinese Open Science Network (COSN): Building an Open Science Community From Scratch 期刊论文  OAI收割 ADVANCES IN METHODS AND PRACTICES IN PSYCHOLOGICAL SCIENCE, 2023, 卷号: 6, 期号: 1, 页码: 17 作者:  Jin, Haiyang;  Wang, Qing;  Yang, Yu-Fang;  Zhang, Han;  Gao, Mengyu (Miranda)   |  收藏  |  浏览/下载：8/0  |  提交时间：2023/10/09 Open Science  grassroots network  non-WEIRD  Chinese  equity-diversity-inclusion (EDI)   Ecosystem responses dominate the trends of annual gross primary productivity over terrestrial ecosystems of China during 2000-2020 期刊论文  OAI收割 AGRICULTURAL AND FOREST METEOROLOGY, 2023, 卷号: 343 作者:  Zhu, Xian-Jin;  Yu, Gui-Rui;  Chen, Zhi;  Zhang, Wei-Kang;  Han, Lang   |  收藏  |  浏览/下载：7/0  |  提交时间：2023/12/01 Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning 期刊论文  OAI收割 SCIENCE OF THE TOTAL ENVIRONMENT, 2023, 卷号: 857 作者:  Zhu, Xian-Jin;  Yu, Gui-Rui;  Chen, Zhi;  Zhang, Wei-Kang;  Han, Lang   |  收藏  |  浏览/下载：18/0  |  提交时间：2024/03/07 Carbon cycle  Climate change  Eddy covariance  Terrestrial ecosystem  Machine learning  Scale extension   A new fossil angiosperm from the Early Cretaceous (early Aptian) of the Zhongkouzi Basin in the Beishan area, Northwest China 期刊论文  OAI收割 HISTORICAL BIOLOGY, 2022, 页码: 11 作者:  Wu, Guang-Tao;  Ren, Wen-Xiu;  Han, Lei;  Wang, Hong-Shan;  Hua, Yi-Fan   |  收藏  |  浏览/下载：33/0  |  提交时间：2022/12/01 Fossil  angiosperm  Early Cretaceous  Northwest China  Chijinpu Formation   Spatiotemporal Pattern of Ecosystem Respiration in China Estimated by Integration of Machine Learning With Ecological Understanding 期刊论文  OAI收割 GLOBAL BIOGEOCHEMICAL CYCLES, 2022, 卷号: 36, 期号: 11, 页码: 15 作者:  Han, Lang;  Yu, Gui-Rui;  Chen, Zhi;  Zhu, Xian-Jin;  Zhang, Wei-Kang   |  收藏  |  浏览/下载：45/0  |  提交时间：2022/12/23 ecosystem respiration  eddy covariance  terrestrial ecosystem  machine learning  substrate  scale extension