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SUMMARY:Machine learning assisted evidence synthesis to support evidence-b
 ased policy on climate change - Dr Max Callaghan\, Mercator Research Insti
 tute on Global Commons and Climate Change\, Berlin
DTSTART:20240123T160000Z
DTEND:20240123T170000Z
UID:TALK209698@talks.cam.ac.uk
CONTACT:Annabelle Scott
DESCRIPTION:Useful information about climate change is hidden in millions 
 of unstructured texts. Using Natural Language Processing (NLP) to identify
 \, classify and analyse these texts\, we can derive insights that help us 
 to understand the science and politics of climate change. Machine learning
 -assisted evidence synthesis can make vital meta-learning from scientific 
 literature more tractable\, and aid important assessment processes like th
 e Intergovernmental Panel on Climate Change. In this talk\, we will explor
 e some of the ways in which machine learning can be used to scale up evide
 nce synthesis\, with applications in climate science\, climate impacts\, a
 nd climate mitigation policy.
LOCATION:Drum Building\, Madingley Rise Site\, West Cambridge and on zoom:
   https://zoom.us/j/6708259482?pwd=Qk03U3hxZWNJZUZpT2pVZnFtU2RRUT09
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