Evidence validation and policy engine for AI-assisted biological curation
C-Rank Grade: B (Solid) - 49/100
External PR Merge Rate: 100%
Response Time: -
First Timer Success: -
NingyuSUN/bioai-evidence-validator has a recorded first-timer success rate of 0.0%. Repositories ranked B typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in NingyuSUN/bioai-evidence-validator 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.
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 48.5 places NingyuSUN/bioai-evidence-validator in the B tier.
The external contributor pull request merge rate for NingyuSUN/bioai-evidence-validator is 100.0%, based on public PR activity from non-core contributors.
NingyuSUN/bioai-evidence-validator currently has 1 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Collaborative maintainer environment in NingyuSUN/bioai-evidence-validator. Reviews community pull requests with focus on project quality.
Discussions in NingyuSUN/bioai-evidence-validator focus heavily on practical implementation feedback, code formatting standards, and issue reproduction details.
Unlinked PRs without issue context and changes that fail automated test suites face the highest review friction.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
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Historical health & responsiveness evolution
External PR acceptance
First PR success rate
50% receive response in
90% receive response in
Maintainer review activity heatmap & prime window prediction
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Maintainers are most responsive around 05:00 UTC (05:00 UTC in your timezone). Recommended submission window is Monday - Wednesday from 05:00 to 09:00 UTC (05:00 - 09:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~16 hours (96% approval). Large PRs (>500 lines) take ~115 hours (45% approval). Keep your diff compact for rapid review.
Since 0.6.0 each extraction_method value carries an ECO term in the LinkML schema (meaning:, see docs/STANDARDS.md), but reports do not show them. Add an opt-in way to include the ECO code for every evidence item in a validation report, so downstream systems that speak ECO can use it directly. Constraints Opt-in only. The default report must stay byte-for-byte identical, because committed benchmark results and audit hashes depend on it. Suggested: bioevidence validate --annotate-eco and a matching keyword argument in Python. Read the codes from the schema (SchemaView(...).get_enum("ExtractionMethod")), do not hard-code them, so the mapping has one source of truth. Where to look src/bioevidence_validator/engine.py (RecordValidator.validate builds the report), src/bioevidence_validator/cli.py tests/test_standards.py shows how to read the meanings Done when With the flag, the report contains, for each evidence item id, its extraction method and ECO CURIE Without the flag, reports a
Contribute a community profile for gene–disease validity, modelled on how ClinGen classifies the strength of a gene–disease relationship (e.g. Definitive, Moderate, Limited, Disputed, Refuted). This is a good first issue for someone with biocuration background; little Python is needed. Where to look How to add one: community/profiles/README.md; copy community/profiles/_template/ Profile fields: docs/PROFILES.md ClinGen Gene-Disease Validity: https://clinicalgenome.org/curation-activities/gene-disease-validity/ (SOP v11 is linked there) The GA4GH VA-Spec has a GeneDiseaseValidityProposition (see docs/STANDARDS.md) Things to decide in the profile README Which intended uses make sense (e.g. a research summary vs. inclusion in a clinical gene panel) and what evidence each requires How the profile's evidence types relate to ClinGen's evidence categories, and what it deliberately does not encode (the profile is not a reimplementation of ClinGen scoring) Done when community/profiles
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When evaluating whether to contribute to NingyuSUN/bioai-evidence-validator, 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 NingyuSUN/bioai-evidence-validator acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 100.0% were successfully merged into the primary branch.
NingyuSUN/bioai-evidence-validator has a recorded first-timer success rate of 0.0%. Repositories ranked Solid typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
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 48.5 places NingyuSUN/bioai-evidence-validator in the Solid tier.
The external pull request merge rate is 100.0%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, NingyuSUN/bioai-evidence-validator currently has 1 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for NingyuSUN/bioai-evidence-validator 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.