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PubMed - Biomedical Research Literature Database
governmentPubMed Central(peer-reviewed)·pubmed.ncbi.nlm.nih.gov/
Credibility Rating
4/5
High(4)High quality. Established institution or organization with editorial oversight and accountability.
Rating inherited from publication venue: PubMed Central
PubMed is a general biomedical literature database; its relevance to AI safety is indirect, primarily as a source for empirical studies on human-AI interaction, automation effects, cognitive science, and related behavioral research.
Metadata
Importance: 30/100homepagereference
Summary
PubMed is the primary public database for biomedical and life sciences literature, maintained by the National Library of Medicine. It indexes millions of citations and abstracts from peer-reviewed journals, serving as a gateway to scientific research across medicine, biology, and related fields.
Key Points
- •Largest freely accessible database of biomedical literature with millions of indexed citations and abstracts
- •Maintained by the U.S. National Library of Medicine, ensuring reliability and comprehensive coverage
- •Relevant to AI safety researchers seeking peer-reviewed studies on human factors, cognitive science, and automation effects
- •Useful for finding empirical research on topics like skill degradation, human-AI interaction, and automation bias
- •Provides access to neuroscience and psychology research that informs alignment and interpretability work
Review
PubMed serves as a critical infrastructure for scientific research, offering an extensive repository of biomedical literature that encompasses citations from MEDLINE, life science journals, and online books. The platform not only provides access to millions of research citations but also continuously evolves its technological capabilities, with recent updates focusing on improved search tools, reference rendering, and user experience enhancements. The platform's significance extends beyond mere citation listing, as it provides links to full-text content, enables advanced searching techniques, and supports researchers through features like clinical queries, citation matching, and API access. Its ongoing improvements, such as synchronizing FTP data with website content and reintroducing customizable email features, demonstrate a commitment to supporting the scientific community's research and information discovery needs.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| AI-Induced Expertise Atrophy | Risk | 65.0 |
Resource ID:
689a9ff80da2437f | Stable ID: NTQwMDNhZD