ArticleeNeuro
Of Mice and Men: Empirical Support for the Population-Based Social Epistasis Amplification Model (a Comment on ).
Article in eNeuro. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
- Comment on
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This commentary article offers new perspective on recent research investigating the behavioral and social ecological effects of a mutation related to autism spectrum disorders in mice. The authors explain the consistency of this research on mice with predictions advanced by a theory of the role of mutations in altering interorganismal gene-gene interactions (social epistasis) in social species including humans, known as the social epistasis amplification model. The potential significance of the mouse research for understanding contemporary human behavioral trends is explored.
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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.