Product walkthrough · 4 min
Assign reviewers without conflicts
Assign reviewers to submissions track by track while the system flags conflicts of interest and shows each reviewer's current workload — so no one reviews their own or a co-author's paper.
Assign reviewers without conflicts walkthrough video
How it works
Step by step
- 1
Open the assignment board for a track
Chairs see every submission in a track alongside the pool of reviewers available for that track.
- 2
Check the conflict flags
Authors and co-authors are automatically blocked from reviewing their own submissions. The system also flags shared affiliations and prior co-authorship as potential conflicts for you to weigh.
- 3
Read workload at a glance
Each reviewer shows how many papers they are already assigned, so you can balance the load instead of overloading your most reliable reviewers.
- 4
Assign reviewers per paper
Assign the number of reviewers each paper needs — for example three. Conflicted reviewers can't be selected, so a bad assignment is prevented up front rather than caught later.
- 5
Use AI suggestions as a shortcut
Optionally pull AI-suggested reviewers ranked by track fit and remaining capacity. Suggestions are advisory only — you confirm each assignment.
- 6
Notify and track progress
Send assignment notifications and watch the board update as reviewers accept, decline, or complete their reviews.
In this walkthrough
What you'll see
- A track-level board mapping submissions to eligible reviewers
- Conflict-of-interest flags that block authors and co-authors automatically
- A live workload count for every reviewer
- Optional AI suggestions that a chair approves before anything is assigned
FAQ
Frequently asked questions
How are conflicts of interest detected?
Authors and co-authors of a submission are blocked from reviewing it automatically. The system additionally flags shared institutional affiliation and recent co-authorship as potential conflicts for the chair to review.
Can I override a flagged conflict?
Hard conflicts — such as an author on the paper — are blocked outright. Softer flags are surfaced with context so the chair can make an informed decision.
Does it support single- and double-blind review?
Yes. Assignment works the same way regardless of blinding; author identities are hidden from reviewers wherever the review model requires it.
What if a reviewer is overloaded?
The workload count is visible during assignment, and AI suggestions factor in remaining capacity, so you can spread reviews evenly across the pool.
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