<div class="csl-bib-body">
<div class="csl-entry">O’Connor, A. M., Clark, J., Thomas, J., Spijker, R., Kusa, W., Walker, V. R., & Bond, M. (2024). Large language models, updates, and evaluation of automation tools for systematic reviews: a summary of significant discussions at the eighth meeting of the International Collaboration for the Automation of Systematic Reviews (ICASR). <i>Systematic Reviews</i>, <i>13</i>, Article 290. https://doi.org/10.1186/s13643-024-02666-2</div>
</div>
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dc.identifier.issn
2046-4053
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/209330
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dc.description.abstract
The eighth meeting of the International Collaboration for the Automation of Systematic Reviews (ICASR) was held on September 7 and 8, 2023, at the University College London, London, England. ICASR is an interdisciplinary group whose goal is to maximize the use of technology for conducting rapid, accurate, and efficient evidence synthesis, e.g., systematic reviews, evidence maps, and scoping reviews of scientific evidence. In 2023, the major themes discussed were understanding the benefits and harms of automation tools that have become available in recent years, the advantages and disadvantages of large language models in evidence synthesis, and approaches to ensuring the validity of tools for the proposed task.
en
dc.language.iso
en
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dc.publisher
BMC
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dc.relation.ispartof
Systematic Reviews
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dc.subject
TAR
en
dc.subject
citation screening
en
dc.subject
evaluation
en
dc.subject
precision at recall
en
dc.subject
normalised precision
en
dc.subject
systematic reviews
en
dc.subject
high-recall retrieval
en
dc.title
Large language models, updates, and evaluation of automation tools for systematic reviews: a summary of significant discussions at the eighth meeting of the International Collaboration for the Automation of Systematic Reviews (ICASR)
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Article
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Artikel
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Other Contribution
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13
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Information Systems Engineering
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100
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Systematic Reviews
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E194-04 - Forschungsbereich Data Science
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10.1186/s13643-024-02666-2
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290
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2046-4053
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7
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E194-04 - Forschungsbereich Data Science
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E194 - Institut für Information Systems Engineering