ArticleGigaScience2017
Science in the cloud (SIC): A use case in MRI connectomics.
Article in GigaScience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 2 citations in OpenAlex.
- ezBIDS: Guided standardization of neuroimaging data interoperable with major data archives and platforms.Scientific data · 2024Article
- Supervised dimensionality reduction for big data.Nature communications · 2021Article
- Article
- Management and Quality Control of Large Neuroimaging Datasets: Developments From the Barcelonaβeta Brain Research Center.Frontiers in neuroscience · 2021Article
- Toward a scalable framework for reproducible processing of volumetric, nanoscale neuroimaging datasets.GigaScience · 2020Article
- Brain structure and cognitive ability in healthy aging: a review on longitudinal correlated change.Reviews in the neurosciences · 2019Review
- Connectome Smoothing via Low-Rank Approximations.IEEE transactions on medical imaging · 2019Article
- The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services.Scientific data · 2019Article
- Container-Based Clinical Solutions for Portable and Reproducible Image Analysis.Journal of digital imaging · 2018Review
- A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data.Frontiers in neuroinformatics · 2018Article
- BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods.PLoS computational biology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught of data, we can allow the focal point to shift from data collection to data analysis. Unfortunately, lack of standardized sharing mechanisms and practices often make reproducing or extending scientific results very difficult. With the creation of data organization structures and tools that drastically improve code portability, we now have the opportunity to design such a framework for communicating extensible scientific discoveries. Our proposed solution leverages these existing technologies and standards, and provides an accessible and extensible model for reproducible research, called 'science in the cloud' (SIC). Exploiting scientific containers, cloud computing, and cloud data services, we show the capability to compute in the cloud and run a web service that enables intimate interaction with the tools and data presented. We hope this model will inspire the community to produce reproducible and, importantly, extensible results that will enable us to collectively accelerate the rate at which scientific breakthroughs are discovered, replicated, and extended.
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.