MCG-NJU/VideoMAE - Open Source PR Review Scorecard

[NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training

C-Rank Grade: D (Risky) - 8/100

External PR Merge Rate: -

Response Time: -

First Timer Success: -

Frequently Asked Questions

Is MCG-NJU/VideoMAE welcoming to first-time open-source contributors?

MCG-NJU/VideoMAE has a recorded first-timer success rate of 0.0%. Repositories ranked D typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in MCG-NJU/VideoMAE respond to incoming external pull requests in approximately 0.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 7.5 C-Rank™ score (D Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 7.5 places MCG-NJU/VideoMAE in the D tier.

What is the external contributor pull request merge rate for MCG-NJU/VideoMAE?

The external contributor pull request merge rate for MCG-NJU/VideoMAE is 0.0%, based on public PR activity from non-core contributors.

Are there Good First Issues available in MCG-NJU/VideoMAE?

MCG-NJU/VideoMAE does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.

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MCG-NJU/VideoMAE

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InactiveD•Risky(8/100)Low Sample (<20 PRs)Python

[NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training

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AI Maintainer Review Guidelines

Review Persona

Empathetic Technical Mentor

Warmth Score
7.5/10
Patience Score
8.2/10
Nitpick Rate
20%

Collaborative maintainer environment in MCG-NJU/VideoMAE. Reviews community pull requests with focus on project quality.

What Contributors Actually Say

Discussions in MCG-NJU/VideoMAE focus heavily on practical implementation feedback, code formatting standards, and issue reproduction details.

Hidden Friction Signals

Unlinked PRs without issue context and changes that fail automated test suites face the highest review friction.

Unwritten Rules

  • •1) Keep PR scope strictly aligned with the linked issue.
  • •2) Ensure local linters pass before opening a review.
  • •3) Maintain full test coverage for modified logic.

Top PR Submission Do's

  • •Ensure code complies with the project coding style
  • •Keep PRs scoped to a single concern
  • •Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit PRs without linking an issue
  • •Do not break existing tests without fixing them
  • •Do not mix unrelated refactors in a single PR
Response Velocity
-
No reviewer activity recorded

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
0.0%
Selective PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
0.0%
No first-timer merges recorded in window

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
CRITICAL BUS FACTOR
Single maintainer
No active GitHub maintainers found (may review internally on Gerrit or internal tools)
Diagnostic Health HUD
0.0%
Merge Gauge
0.0%
1st-Timer
Community Vibe0/100

Embed C-Rank Badge

Show contributors that your repository actively reviews and merges external pull requests.

GetMerged C-Rank badge for MCG-NJU/VideoMAE
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/MCG-NJU/VideoMAE)](https://getmerged.abhishekco.de/MCG-NJU/VideoMAE?utm_source=github&utm_medium=badge)

Active Good First Issues (0)

View on GitHub

No cached good first issues currently tracked for MCG-NJU/VideoMAE.

View all good first issues directly on GitHub

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Contributor Community Vibe Feedback

Rate what actually matters after opening a pull request here.

Have you contributed to this repo?

Rate your first-hand PR experience (review speed, maintainer responsiveness, and onboarding ease) to help other contributors.

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Maintainer helpfulness
Review speed
Beginner friendliness

Contributor Compatibility & Review Speed Analysis for MCG-NJU/VideoMAE

When evaluating whether to contribute to MCG-NJU/VideoMAE, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of MCG-NJU/VideoMAE acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 0.0% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to MCG-NJU/VideoMAE

01

Is MCG-NJU/VideoMAE welcoming to first-time open-source contributors?

MCG-NJU/VideoMAE has a recorded first-timer success rate of 0.0%. Repositories ranked Risky typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 7.5 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 7.5 places MCG-NJU/VideoMAE in the Risky tier.

04

What is the external contributor pull request merge rate for MCG-NJU/VideoMAE?

The external pull request merge rate is 0.0%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in MCG-NJU/VideoMAE?

MCG-NJU/VideoMAE does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for MCG-NJU/VideoMAE are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.