ArticleClinical science (London, England : 1979)2021
Time to fiddle with your unpublished data.
Article in Clinical science (London, England : 1979), 2021. 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
- Comment on
Authors and funding
2 authors.
Funding
Abstract
Most scientific investigators conduct well-designed and controlled preclinical experiments generating data that are difficult to explain, contrast with existing scientific dogma, or represent a perceived negative result. It is common for these findings to remain hidden away in a drawer from the greater scientific community. However, these unseen results can lead to publication bias, have the potential to significantly advance scientific disciplines if they are published, and can help investigators avoid repeating experiments that have already been done, thus saving money and time. Moreover, these unexpected data may actually have significance if re-interpreted leading to new hypotheses. This editorial commentary highlights a novel user-friendly tool developed by Bernard and colleagues (REF) to help investigators determine appropriate options for disseminating unpublished data in order to make them available to the broader scientific community. In addition, this commentary serves as an announcement for an upcoming special call for papers on meta-research to be published in Clinical Science. Meta-research is the evaluation and study of existing scientific literature and data. It is an evolving field dedicated to improving rigor and reproducibility in science, an endeavor to which Clinical Science and Portland Press are committed.
Indexed as
Identifiers
33404049What 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.