ArticleToxics2025
Semi-Correlations for the Simulation of Dermal Toxicity.
Article in Toxics, 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
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The skin is the primary pathway for harmful substances to enter the body and a susceptible target organ, making compound-induced acute dermal toxicity a significant health risk. In this work, the possibility of modelling dermal toxicity using so-called semi-correlations is studied. Semi-correlations are a specific case of correlations, where one variable takes only two values. For example, 0 denotes the absence of activity (e.g., dermal toxicity), and 1 denotes the presence of activity. The described computational experiments can be carried out by interested readers using the freely available software CORAL.
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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.