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Methods & Data Coverage

How we process, validate and present space biology evidence

DATA FOUNDATION

  • 572 peer-reviewed publications from NASA spaceflight studies aggregated from OSDR, PSI, GeneLab, and PubMed Central
  • 245 OSDR dataset cross-references linking publications to raw experimental data
  • 156 GeneLab datasets with genomic and transcriptomic profiles
  • 87 Task Book entries tracking ongoing research projects
  • Full-text XML articles parsed from NASA repositories and open science databases
  • Metadata extraction includes authors, publication dates, funding sources, and experimental conditions

EVIDENCE PROCESSING PIPELINE

  • Section-level parsing using IMRaD structure (Introduction, Methods, Results, Discussion)
  • 2,165 evidence spans extracted and tagged: Abstract (702), Results (386), Methods (385), Discussion (276), Introduction (218), Conclusion (198)
  • Section-aware retrieval where Results sections are prioritized for factual claims
  • Semantic embeddings generated for each evidence span to enable similarity search
  • Entity extraction identifies biological systems, experimental conditions, and measured outcomes
  • Automated classification of evidence type (observational, experimental, review, meta-analysis)

KNOWLEDGE GRAPH CONSTRUCTION

  • 28,864 evidence relations (supports/contradicts) extracted using natural language processing
  • Graph structure maps agreement and disagreement across studies
  • Node types include publications, biological systems, experimental conditions, and findings
  • Edge types capture relationships: supports, contradicts, extends, replicates, reviews
  • Citation network analysis identifies influential studies and research clusters
  • Temporal tracking shows how consensus evolves over time

AUTOMATED GAP IDENTIFICATION

  • Coverage analysis identifies under-studied biological systems and experimental conditions
  • Contradiction detection flags conflicting findings that require resolution
  • Mission-critical gaps prioritized based on relevance to lunar, Mars, and ISS operations
  • Statistical power analysis identifies areas where more replication is needed
  • Temporal gap analysis shows where recent research is lacking
  • Cross-system gap detection identifies biological interactions that remain unexplored

QUALITY ASSURANCE & VALIDATION

  • Automated section classification with manual validation for edge cases
  • Citation tracking across the corpus to identify consensus and outliers
  • Contradiction detection flags conflicting findings for expert review
  • Source reliability scoring based on journal impact factor, citation count, and peer review status
  • Confidence scores assigned to each finding based on evidence strength and replication
  • Regular audits of extraction accuracy and relation classification performance

MISSION APPLICATIONS

  • Mission-specific filtering enables targeted evidence retrieval for lunar, Mars, and ISS scenarios
  • Risk assessment support by identifying known hazards and mitigation strategies
  • Countermeasure evaluation through evidence synthesis across multiple studies
  • Timeline-aware recommendations based on mission phase (pre-flight, in-flight, post-flight)
  • Integration with NASA mission planning tools and decision support systems
  • Automated briefing generation for mission planners and flight surgeons

Open Science

This project follows open science principles. Our methodology is fully documented, and we plan to release processed datasets and analysis code under open licenses to enable reproducibility and community contributions.