We are a research team from San José State University and Sacramento State University conducting a methodological study to evaluate the diagnostic accuracy of open-source AI models for title and abstract screening when conducting scoping reviews on topics related to the allied health sciences.
We identified your scoping review as a high-quality example of human expert screening. We are writing to ask if you would be open to contributing your de-identified screening data to serve as a "reference standard" for our study.
If you are interested in collaborating, please complete this 2-minute eligibility check: https://forms.gle/hrjKmgkaRX2BkhWx6
(If you have multiple reviews that meet these criteria, please submit a separate form for each project.)
This brief form will confirm if your dataset aligns with our specific study protocol (e.g., JBI methodology). You can view our full protocol here: https://osf.io/9s2nj/files/uk6vc.
Thank you for your time and contribution to evidence synthesis methodology.
Sincerely,
Somayeh Shahsavarani, Amith Kamath Belman, and Dawn Hackman from San José State University (San José, CA, USA), and Laura Gaeta and Rachel Keiko Stark from Sacramento State University (Sacramento, CA, USA)
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Rachel Keiko Stark
Health Sciences Librarian
California State University, Sacramento
She/Her/Hers,They/Them/Theirs,My name
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