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DDA Cross-Package Handbook

This page follows one real flagship DDA path across all six product packages so the reader does not need to open seven separate handbooks before they can see how the repository actually cooperates.

One Benchmark Path

owner question this owner answers on the DDA path best evidence surface
bijux-proteomics-foundation Which identifiers, JSON envelopes, and deterministic hashes keep the DDA evidence chain stable across packages? bijux-proteomics-foundation Foundation
bijux-proteomics-core Which copied benchmark package, acceptance bars, and workflow contracts define the DDA scientific lane? DDA Benchmark Lineage and Flagship Acceptance Bars
bijux-proteomics-runtime Which DDA execution lane is actually supported today, and what does the current rerun limit still block? Black-Box Benchmark Dashboard and Runtime Execution Boundary
bijux-proteomics-knowledge Which references, comparators, and contradictions still ground the DDA sentence? Workflow Claim Grounding and Workflow Literature Audits
bijux-proteomics-intelligence Which recommendation pressure, downgrade logic, and outsider challenge surfaces keep DDA language bounded? Workflow Recommendation Confidence and Workflow Recommendation Challenges
bijux-proteomics-lab Which assay burden and follow-up consequence still cap the DDA story downstream? Workflow Consequence Maps and Outcome Learning Loops

Why DDA Stops Where It Stops

  • The current DDA run mode is import_only, so runtime truth still depends on imported external-engine output rather than an in-repository raw search lane.
  • Core still owns the benchmark lineage and acceptance language, which keeps DDA from sounding broader than the current package and challenge evidence.
  • Knowledge and intelligence keep the DDA sentence honest by carrying comparator pressure, reference support, and downgrade triggers.
  • Lab consequence remains narrower than a fully raw-executable family because the assay burden and downstream support still depend on imported search truth.

Next Routes