Do a sweep over openneuro priority datasets
Open
- Dominant language
- Python
- Stars
- 1
- Forks
- 4
- Avg merge
- 15h 39m
- Merged PRs (30d)
- 24
Description
- doing 1 subject (session) per each one of the priority datasets with
- 1 minimal and 1 full (we need to assess)
Contributor guide
No contributing guide indexed for this repository
Research direction
The issue does not name any files, tests, entry points, priority datasets, or expected outputs. Start by locating how datasets and BAB runs are selected and recorded, then identify the priority dataset list and clarify what “minimal” and “full” mean. Done means one subject or session has been run in both modes for every priority dataset, with the assessment captured.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 45/100