Goals and Strategies for the Indexing of Publication Types and Study Designs
Neil R. Smalheiser, Joe D. Menke, Arthur W. Holt, Halil Kilicoglu, Jodi Schneider

TL;DR
This paper discusses the unique goals and challenges of indexing publication types and study designs in biomedical literature, emphasizing the need for comprehensive, probabilistic, and automated approaches to improve retrieval and evidence synthesis.
Contribution
It introduces a unified hierarchy for publication types and study designs and highlights the importance of probabilistic scoring for automated indexing systems.
Findings
Created a unified hierarchy for publication types and study designs.
Emphasized the need for probabilistic goodness-of-fit prediction scores.
Proposed automated systems for real-time, comprehensive PT indexing.
Abstract
Objectives. Major research and implementation efforts have been devoted to indexing articles according to the major topics discussed, but much less effort to indexing their publication types and study designs (collectively, PTs). In this Perspective, we discuss how indexing PTs differs from topical MeSH indexing and requires a different approach. Materials and Methods. Rather than focus on the technical aspects of machine learning-based indexing models, we emphasize the goals and purposes for which biomedical articles are indexed, and the surprisingly thorny question of how indexing systems should be evaluated. Results. Topical Medical Subject Heading (MeSH) terms are assigned to articles that cover the major topics discussed; when more than one term is applicable, only the most specific term is assigned. In contrast, PTs are assigned to articles that have a given structure or use a…
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