ArticlePLoS biology2020
Ten tips for a text-mining-ready article: How to improve automated discoverability and interpretability.
Article in PLoS biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Delving into the Practical Applications and Pitfalls of Large Language Models in Medical Education: Narrative Review.Advances in medical education and practice · 2025Review
- Chemical identification and indexing in full-text articles: an overview of the NLM-Chem track at BioCreative VII.Database : the journal of biological databases and curation · 2023Article
- Comprehensively identifying Long Covid articles with human-in-the-loop machine learning.Patterns (New York, N.Y.) · 2023Article
- Toward reporting standards for the pathogenicity of variant combinations involved in multilocus/oligogenic diseases.HGG advances · 2023Review
- New reasons for biologists to write with a formal language.Database : the journal of biological databases and curation · 2022Article
- Recent advances of automated methods for searching and extracting genomic variant information from biomedical literature.Briefings in bioinformatics · 2021Review
- A Second Look at FAIR in Proteomic Investigations.Journal of proteome research · 2021Article
- LitCovid: an open database of COVID-19 literature.Nucleic acids research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Data-driven research in biomedical science requires structured, computable data. Increasingly, these data are created with support from automated text mining. Text-mining tools have rapidly matured: although not perfect, they now frequently provide outstanding results. We describe 10 straightforward writing tips-and a web tool, PubReCheck-guiding authors to help address the most common cases that remain difficult for text-mining tools. We anticipate these guides will help authors' work be found more readily and used more widely, ultimately increasing the impact of their work and the overall benefit to both authors and readers. PubReCheck is available at http://www.ncbi.nlm.nih.gov/research/pubrecheck.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.