Evaluating Causal Discovery Algorithms for Path-Specific Fairness and Utility in Healthcare
Compared to this week’s papers
Stale evidence
Evidence Receipt
Freshness: 2026-04-02T02:30:40.136932+00:00Claims: 0
References: 0
Proof: partial
Freshness: stale
Source paper: Evaluating Causal Discovery Algorithms for Path-Specific Fairness and Utility in Healthcare
PDF: https://arxiv.org/pdf/2603.15926v1
Repository: https://github.com/nitish-nagesh/causal-discovery-fairness
Source count: 0
Coverage: 50%
Last proof check: 2026-03-18T22:54:36.415Z
Paper Conversation
Citation-first answers with explicit evidence receipts, disagreement handling, commercialization framing, and next actions.
Evaluating Causal Discovery Algorithms for Path-Specific Fairness and Utility in Healthcare
Canonical Paper Receipt
Last verification: 2026-03-18T22:54:36.415ZFreshness: stale
Proof: partial
Repo: active
References: 0
Sources: 0
Coverage: 50%
- - references
- - distribution_readiness_scores
- - paper_extraction_scorecards
- - distribution readiness has not been computed yet
Starting…
Dimensions overall score 4.0
GitHub Code Pulse
Claim map
Claim extraction is still pending for this paper. Check back after the next analysis run.
Competitive landscape
Competitor map is still being generated for this paper. Enable generation or check back soon.
Startup potential card
Related Resources
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
Lightweight coding agent in your terminal.
Agentic coding tool for terminal workflows.
AI agent mindset installer and workflow scaffolder.
AI-first code editor built on VS Code.
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $10K - $14K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.