A Similarity Metric, Rubric and Unified Hierarchy for Biomedical Publication Types and Study Designs

The similarity metric has the potential to improve the modeling, implementation and evaluation of automated indexing systems. The PT rubric provides an overview that complements the existing NIH MeSH Hierarchy trees, and the unified hierarchy permits proper automated expansion for PT indexing and PubMed user queries involving PT terms.

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Publication Details

Journal
medRxiv
Published
2026-01-04
DOI
https://doi.org/10.64898/2026.01.03.26343378
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00

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article

A Similarity Metric, Rubric and Unified Hierarchy for Biomedical Publication Types and Study Designs

Neil R. Smalheiser, Arthur W. Holt, Joe D Menke
medRxiv
Biomedical Text Mining and Ontologies
article

A Similarity Metric, Rubric and Unified Hierarchy for Biomedical Publication Types and Study Designs

Neil R. Smalheiser, Arthur W. Holt, Joe D Menke
article en

Abstract

The similarity metric has the potential to improve the modeling, implementation and evaluation of automated indexing systems. The PT rubric provides an overview that complements the existing NIH MeSH Hierarchy trees, and the unified hierarchy permits proper automated expansion for PT indexing and PubMed user queries involving PT terms.

medRxiv
University of Illinois Urbana-Champaign (US), University of Illinois Chicago (US), University of Chicago (US)
National Institutes of Health, U.S. National Library of Medicine
Openalex Percentile: Top 97%
Biomedical Text Mining and Ontologies
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