Publication Date
In 2025 | 0 |
Since 2024 | 2 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 3 |
Since 2006 (last 20 years) | 3 |
Descriptor
Computer Software | 3 |
Research Reports | 3 |
Artificial Intelligence | 2 |
Meta Analysis | 2 |
Accuracy | 1 |
Authors | 1 |
Biology | 1 |
Case Studies | 1 |
Classification | 1 |
Comparative Analysis | 1 |
Computational Linguistics | 1 |
More ▼ |
Source
Research Synthesis Methods | 3 |
Author
Azza Warraitch | 1 |
Christine J. Neilson | 1 |
Heger, Tina | 1 |
Jeschke, Jonathan M. | 1 |
Johanna Kappenberg | 1 |
Kristin Hadfield | 1 |
Qusai Khraisha | 1 |
Rillig, Matthias C. | 1 |
Ryo, Masahiro | 1 |
Sophie Put | 1 |
Zahra Premji | 1 |
More ▼ |
Publication Type
Journal Articles | 3 |
Reports - Research | 3 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Christine J. Neilson; Zahra Premji – Research Synthesis Methods, 2024
The literature search underpins data collection for all systematic reviews (SRs). The SR reporting guideline PRISMA, and its extensions, aim to facilitate research transparency and reproducibility, and ultimately improve the quality of research, by instructing authors to provide specific research materials and data upon publication of the…
Descriptors: Search Strategies, Information Retrieval, Guidelines, Computer Software
Qusai Khraisha; Sophie Put; Johanna Kappenberg; Azza Warraitch; Kristin Hadfield – Research Synthesis Methods, 2024
Systematic reviews are vital for guiding practice, research and policy, although they are often slow and labour-intensive. Large language models (LLMs) could speed up and automate systematic reviews, but their performance in such tasks has yet to be comprehensively evaluated against humans, and no study has tested Generative Pre-Trained…
Descriptors: Peer Evaluation, Research Reports, Artificial Intelligence, Computer Software
Ryo, Masahiro; Jeschke, Jonathan M.; Rillig, Matthias C.; Heger, Tina – Research Synthesis Methods, 2020
Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free statistical modeling of artificial intelligence, is a promising synthesis tool for discovering novel…
Descriptors: Artificial Intelligence, Case Studies, Biology, Research Reports