ArticleeLife2015
Overflow in science and its implications for trust.
Article in eLife, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Article
- Protection of the human gene research literature from contract cheating organizations known as research paper mills.Nucleic acids research · 2022Review
- On the objectivity, reliability, and validity of deep learning enabled bioimage analyses.eLife · 2020Article
- On Some Possible Ramifications of the "Microplastics in Fish" Case.Science and engineering ethics · 2019Article
- Guidelines for Experiments Using Antisense Oligonucleotides and Double-Stranded RNAs.Nucleic acid therapeutics · 2019Article
- The Possibility of Systematic Research Fraud Targeting Under-Studied Human Genes: Causes, Consequences, and Potential Solutions.Biomarker insights · 2019Review
- Fecal Carriage of Staphylococcus aureus in the Hospital and Community Setting: A Systematic Review.Frontiers in microbiology · 2016Review
- Improving the peer review of narrative literature reviews.Research integrity and peer review · 2016Article
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
Abstract
To explore increasing concerns about scientific misconduct and data irreproducibility in some areas of science, we interviewed a number of senior biomedical researchers. These interviews revealed a perceived decline in trust in the scientific enterprise, in large part because the quantity of new data exceeds the field's ability to process it appropriately. This phenomenon-which is termed 'overflow' in social science-has important implications for the integrity of modern biomedical science.
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.