AI-Powered Meta-Analysis Automation
AI-Powered Meta-Analysis Automation accelerates evidence synthesis in agriculture by automating the repetitive stages of a review while preserving methodological rigor. The workflow covers: search-term generation, LLM-assisted screening, tagging, keyword extraction, classification, and harmonization...
| Autores principales: | , , , |
|---|---|
| Formato: | Conjunto de datos |
| Lenguaje: | Inglés |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/180145 |
| _version_ | 1855533100094717952 |
|---|---|
| author | Muller, Lolita Joshi, Namita Steward, Peter Richard Rosenstock, Todd Stuart |
| author_browse | Joshi, Namita Muller, Lolita Rosenstock, Todd Stuart Steward, Peter Richard |
| author_facet | Muller, Lolita Joshi, Namita Steward, Peter Richard Rosenstock, Todd Stuart |
| author_sort | Muller, Lolita |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | AI-Powered Meta-Analysis Automation accelerates evidence synthesis in agriculture by automating the repetitive stages of a review while preserving methodological rigor. The workflow covers: search-term generation, LLM-assisted screening, tagging, keyword extraction, classification, and harmonization. Outputs are systematically compared with expert manual reviews to quantify quality and relevance, clarifying where automation performs well and where caution is warranted. |
| format | Conjunto de datos |
| id | CGSpace180145 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| record_format | dspace |
| spelling | CGSpace1801452026-01-19T16:22:57Z AI-Powered Meta-Analysis Automation Muller, Lolita Joshi, Namita Steward, Peter Richard Rosenstock, Todd Stuart agriculture agricultura artificial intelligence inteligencia artificial meta-analysis large language models-llms metaanálisis AI-Powered Meta-Analysis Automation accelerates evidence synthesis in agriculture by automating the repetitive stages of a review while preserving methodological rigor. The workflow covers: search-term generation, LLM-assisted screening, tagging, keyword extraction, classification, and harmonization. Outputs are systematically compared with expert manual reviews to quantify quality and relevance, clarifying where automation performs well and where caution is warranted. 2025-10-14 2026-01-19T16:22:56Z 2026-01-19T16:22:56Z Dataset https://hdl.handle.net/10568/180145 en Open Access Muller, L.; Joshi, N.; Steward, P.R.; Rosenstock, T.S. (2025) AI-Powered Meta-Analysis Automation. https://doi.org/10.5281/zenodo.17348596 |
| spellingShingle | agriculture agricultura artificial intelligence inteligencia artificial meta-analysis large language models-llms metaanálisis Muller, Lolita Joshi, Namita Steward, Peter Richard Rosenstock, Todd Stuart AI-Powered Meta-Analysis Automation |
| title | AI-Powered Meta-Analysis Automation |
| title_full | AI-Powered Meta-Analysis Automation |
| title_fullStr | AI-Powered Meta-Analysis Automation |
| title_full_unstemmed | AI-Powered Meta-Analysis Automation |
| title_short | AI-Powered Meta-Analysis Automation |
| title_sort | ai powered meta analysis automation |
| topic | agriculture agricultura artificial intelligence inteligencia artificial meta-analysis large language models-llms metaanálisis |
| url | https://hdl.handle.net/10568/180145 |
| work_keys_str_mv | AT mullerlolita aipoweredmetaanalysisautomation AT joshinamita aipoweredmetaanalysisautomation AT stewardpeterrichard aipoweredmetaanalysisautomation AT rosenstocktoddstuart aipoweredmetaanalysisautomation |