Type
Funder
Country
—
ROR
—
Documents
4
through any edge
Papers
0
authorship edges
Awards made
7
7 grant numbers
Named as funder
4
no grant number
Identifiers
Funding
Read from the funding tables, never from the document count — that count includes authorship, so it ranks institutions, not funders.
What Maternal and Child Health Bureau has funded
7 awards under 7 distinct grant numbers, across 1 documents. A further 4 documents name it as a funder without a grant number — a weaker claim, counted separately.
Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant U03MC00001 · 2025-02-20Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant U03MC00007 · 2025-02-20Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant U03MC22684 · 2025-02-20Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant U03MC28844 · 2025-02-20Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant U03MC33154 · 2025-02-20Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant U03MC33156 · 2025-02-20Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant UJ5MC30824 · 2025-02-20
7 of 11 funding edges