ReviewBrain research bulletin2023
Reframing the perception of outliers and negative data in translational research.
Review in Brain research bulletin, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Replicable generation and stable maintenance of rhesus macaque iPSCs forFrontiers in cell and developmental biology · 2026Article
- Position paper: leveraging non-human primate (NHP) specificities to accelerate Parkinson's disease and ageing research.NPJ Parkinson's disease · 2025Review
- Eleven quick tips to unlock the power of in vivo data science.PLoS computational biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Negative results can be a source of disappointment for scientists, yet their publication is needed for scientific progress, in particular for cutting-edge translational research of novel therapeutics. This manuscript is directed to scientists, junior and senior, that produce and review data for publication. It discusses the difference between 'negative' or 'unexpected' data and 'useless' data, re-evaluates the importance of the experimental design to generate valuable data and proposes strategies to work with and report negative results. Overall, it aims to reframe the perception of working with, reporting and reviewing unexpected data as an opportunity to provide rationale for innovative ideas, prevent the misuse of limited resources and, ultimately, strengthen the reputation of a scientist.
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.