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Impact of High-quality, Deeply Curated Data on Biomedical Data Discoverability

Key Highlights

  • In recent years, there has been notable progress in LLMs, sparking enthusiasm for integrating these models with extensive databases for natural language-based information retrieval.
  • Discussions on effective search typically spotlight the model's reasoning abilities, but it's vital to highlight metadata quality's role in enabling effective search.
  • This whitepaper presents a case study on data discoverability in a large corpus of gene expression data, and the impact of metadata annotation quality on search outcomes.
  • Elucidata's meticulous metadata curation yields precise responses to intricate user queries, significantly shaping AI models' search capabilities through curated data accessibility.

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