Downloads provided by UsageCountsSupplementary Data: Sensitivity of Air Pollution Exposure and Disease Burden to Emission Changes in China using Machine Learning Emulation.
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UKRI| EXHALE: EXploiting new understanding of Heterogeneous production of reactive species from AIRPRO: Links to haze and human health Effects
Conibear, L.; Reddington, C. L; Silver, B. J.; Chen, Y.; Arnold, S. R.; Spracklen, D. V.;
Supplementary Data: Sensitivity of Air Pollution Exposure and Disease Burden to Emission Changes in China using Machine Learning Emulation.
Temporary duplicate of: Conibear, L., Reddington, C. L., Silver, B. J., Chen, Y., Arnold, S. R., & Spracklen, D. V. (2022). Supplementary Data: Sensitivity of Air Pollution Exposure and Disease Burden to Emission Changes in China using Machine Learning Emulation. University of Leeds. [Dataset]. https://doi.org/doi.org/10.5518/1055
- University of Leeds United Kingdom
- University of Exeter United Kingdom
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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