Table 4. Potential pros and cons of the main features of the peer review models that are discussed.

Note that some of these are already employed, alone or in combination, by different research platforms.

Feature	Description	Pros	Cons/Risks	Existing models
Voting or rating	Quantified review evaluation (5 stars, points), including up- and down-votes	Community-driven, quality filter, simple and efficient	Randomized procedure, auto-promotion, gaming, popularity bias, non-static	Reddit, Stack Exchange, Amazon
Openness	Public visibility of review content	Responsibility, accountability, context, higher quality	Peer pressure, potential lower quality, invites retaliation	All
Reputation	Reviewer evaluation and ranking (points, review statistics)	Quality filter, reward, motivation	Imbalance based on user status, encourages gaming, platform-specific	Stack Exchange, GitHub, Amazon
Public commenting	Visible comments on paper/ review	Living/organic paper, community involvement, progressive, inclusive	Prone to harassment, time consuming, non- interoperable, low re-use	Reddit, Stack Exchange, Hypothesis
Version control	Managed releases and configurations	Living/organic objects, verifiable, progressive, well- organized	Citation tracking, time consuming, low trust of content	GitHub, Wikipedia
Incentivization	Encouragement to engage with platform and process via badges/money or recognition	Motivation, return on investment	Research monetization, can be perverted by greed, expensive	Stack Exchange, Blockchain
Authentication and certification	Filtering of contributors via verification process	Fraud control, author protection, stability	Difficult to manage	Blockchain
Moderation	Filtering of inappropriate behavior in comments, rating	Community-driven, quality filter	Censorship, mainstream speech	Reddit, Stack Exchange