Koch, Marta;
(2025)
Low-Cost, High-Impact Public Sector Innovation: Utilising the Full Potential of GenAI Large Language Models (LLMs) for Smarter Multi-Level Environmental Monitoring.
(UN OICT Unite Research Brief
).
UN Office of Information and Communications Technology (OICT): New York, NY, USA.
(In press).
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| Type: | Working / discussion paper |
|---|---|
| Title: | Low-Cost, High-Impact Public Sector Innovation: Utilising the Full Potential of GenAI Large Language Models (LLMs) for Smarter Multi-Level Environmental Monitoring |
| Publisher version: | https://unite.un.org/ |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10211244 |
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