ArticleeLife2016
Publication bias and the canonization of false facts.
Article in eLife, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 6 of them syntheses that pooled it.
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
80 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Low reporting quality limits the contribution of human organ models to COVID-19 research: a systematic review.EBioMedicine · 2026Pooled it
- Structural and functional brain abnormal alteration in patients with type 2 diabetes mellitus: A coordinate-based meta-analysis.Translational psychiatry · 2025Pooled it
- Estimation of moral distress among nurses: A systematic review and meta-analysis.Nursing ethics · 2023Pooled it
- Methodological Challenges to the Evaluation of Interventions for Foster/Kinship Carers and Children: A Systematic Review.Clinical child and family psychology review · 2018Pooled it
- Pooled it
- The relationship between physician burnout and quality of healthcare in terms of safety and acceptability: a systematic review.BMJ open · 2017Pooled it
- Is Ashwagandha an Abortifacient?Phytotherapy research : PTR · 2026Article
- External validation improves generalizability, replicability and reproducibility in predictive models for neuroimaging.Nature methods · 2026Review
- Canonical fact versus hypothesis testing to decipher transmission of non-tuberculous and tuberculous mycobacteria: a comparative review.Clinical microbiology reviews · 2025Review
- Extracellular Vesicles and the Gartner Hype Cycle.Journal of extracellular biology · 2025Article
- Estimating the Replicability of Sports and Exercise Science Research.Sports medicine (Auckland, N.Z.) · 2025Article
- Early career setback and future achievement in professional sports.Scientific reports · 2025Article
- Ending publication bias: A values-based approach to surface null and negative results.PLoS biology · 2025Article
- How thoughtful experimental design can empower biologists in the omics era.Nature communications · 2025Review
- Potential Obstacles and Strategic Interventions for Addressing Gaps in the Understanding of Human-Artificial Intelligence Interactions in Medical Practice.Korean journal of radiology · 2025Article
- Fostering trustworthy information: countering disinformation when there are no bare facts.Royal Society open science · 2025Article
- Review
- Statistics in Service of Metascience: Measuring Replication Distance with Reproducibility Rate.Entropy (Basel, Switzerland) · 2024Article
- Better nanoscience through open, collaborative, and critical discussions.Materials horizons · 2024Review
- Invasive ant learning is not affected by seven potential neuroactive chemicals.Current zoology · 2024Article
20 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Science is facing a "replication crisis" in which many experimental findings cannot be replicated and are likely to be false. Does this imply that many scientific facts are false as well? To find out, we explore the process by which a claim becomes fact. We model the community's confidence in a claim as a Markov process with successive published results shifting the degree of belief. Publication bias in favor of positive findings influences the distribution of published results. We find that unless a sufficient fraction of negative results are published, false claims frequently can become canonized as fact. Data-dredging, p-hacking, and similar behaviors exacerbate the problem. Should negative results become easier to publish as a claim approaches acceptance as a fact, however, true and false claims would be more readily distinguished. To the degree that the model reflects the real world, there may be serious concerns about the validity of purported facts in some disciplines.
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.