Reviewer AI - the first piece of the standard to reach the public
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The Women's Health Research Standard™, applied. Any researcher, clinician, or woman can score a paper in minutes — and finally know what the evidence is actually worth.
Hormonal contraception and mood outcomes in women aged 18–35
Journal of Women's Health · 2024
WHRS™ Score breakdown
What you get
A complete analysis of any paper
Every report covers eight dimensions — from plain-language summary to a full WHRS™ Score — so you know exactly how well a study applies to women.
Summary
What the study did and found, in plain language.
Limitations
What the study cannot tell you about women.
Women-focused research critique
Whether the design, inclusion, sampling, data collection, controls, statistical rigor, and outcomes were appropriate for female subjects — and to what extent.
Bias analysis
Funding, selection, measurement, and reporting bias — including sex and gender bias.
Citation quality
How solid the evidence base underneath the paper is.
Key figures
The numbers that matter, extracted and explained.
Overall WHRS™ Score
Quality and applicability of the study, graded on the Women's Health Research Standard.
AI Q&A
Ask follow-up questions about the paper.
Who it's for
Built for all women's health stakeholders
Women
Understand how well a study actually applies to you — and how strong it is — so you can make better-informed decisions about your health.
Clinicians & practitioners
Screen the evidence behind a protocol before you recommend it to a woman or female population.
Researchers & students
Methodology critique, bias analysis, and citation quality on demand — a rigorous women-focused analysis of any paper.
Health writers & advocates
Know how strong a study really is before you cite it. The score tells the story.
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Join waitlistThe Women's Health Research Reviewer AI is an educational and research-screening tool — not medical advice, diagnosis, or treatment. Reports are AI-generated and may contain errors; they are not a substitute for expert peer review. Scores are automated assessments of research quality, not endorsements or refutations of a study's findings.