ArticleF1000Research2025
Abstract Sifter version 8: Focus on the chemical literature.
Article in F1000Research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Effective research depends on building on the knowledge found in the scientific literature. Designed to streamline literature tasks, the EPA's Abstract Sifter literature tool, now at version 8, has been continually extended and enhanced since its introduction in 2017[1]. Early enhancements to the tool have primarily focused on core tasks common to all researchers. For example, citation retrieval from PubMed has been made faster and the returned citation threshold increased to 10,000. Features that allow deeper examination of the literature have been introduced as well. A functionality called Term-mapping allows for fast, dynamic relevancy ranking of returned citations. MeSH substances, such as proteins, genes, and chemicals, can now be extracted from a retrieved corpus of citations, ranked by frequency and explored through the MeSHMine functionality. Features that facilitate user engagement with publications have also been improved: formatting and colorization ease reviewing of the abstract text and the tagging and noting citations functionality has been streamlined. Version 8 introduced multiple features that break new ground in working with chemical literature. For example, chemical entity extraction from scientific publications has been streamlined through download of PDFs and automated table extraction. Following entity extraction, the chemical names can be used as inputs to retrieve EPA's chemical identifiers, the DSSTox (Distributed Structure-Searchable Toxicity) chemical IDs (DTXSIDs). Once these identifiers have been retrieved, a wealth of chemical information is available through built-in functions accessing EPA's Computational Toxicology and Exposure application programming interface (CTX-APIs) [2]. This new functionality allows researchers to build on the EPA's efforts in chemical data assembly and curation. The Abstract Sifter version 8 is a valuable tool for researchers endeavoring to understand chemicals and their effects on the environment and biological systems.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.