ArticleMetabolites2023
SMetaS: A Sample Metadata Standardizer for Metabolomics.
Article in Metabolites, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Integrating multi-omics technologies to decipher microbiome functions.Nature communications · 2026Review
- Current state of data stewardship tools in life science.Frontiers in big data · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Metabolomics has advanced to an extent where it is desired to standardize and compare data across individual studies. While past work in standardization has focused on data acquisition, data processing, and data storage aspects, metabolomics databases are useless without ontology-based descriptions of biological samples and study designs. We introduce here a user-centric tool to automatically standardize sample metadata. Using such a tool in frontends for metabolomic databases will dramatically increase the FAIRness (Findability, Accessibility, Interoperability, and Reusability) of data, specifically for data reuse and for finding datasets that share comparable sets of metadata, e.g., study meta-analyses, cross-species analyses or large scale metabolomic atlases. SMetaS (Sample Metadata Standardizer) combines a classic database with an API and frontend and is provided in a containerized environment. The tool has two user-centric components. In the first component, the user designs a sample metadata matrix and fills the cells using natural language terminology. In the second component, the tool transforms the completed matrix by replacing freetext terms with terms from fixed vocabularies. This transformation process is designed to maximize simplicity and is guided by, among other strategies, synonym matching and typographical fixing in an n-grams/nearest neighbors model approach. The tool enables downstream analysis of submitted studies and samples via string equality for FAIR retrospective use.
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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.