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Known Limitations

Known limitations matter because honest boundaries are part of quality, not an admission of failure.

For bijux-proteomics-intelligence, limitations exist wherever recommendation quality depends on evidence strength, operator judgment, or downstream execution outside this package.

Limitation Model

flowchart TB
    evidence["weak or conflicting evidence"]
    policy["intelligence policy and evaluators"]
    outputs["rankings, reports, and outcomes"]
    execution["lab and runtime execute the result"]
    limit["intelligence cannot turn weak inputs into guaranteed truth"]

    evidence --> policy
    policy --> outputs
    outputs --> execution
    evidence --> limit
    execution --> limit

This page should stop readers from over-claiming what a scoring layer can do. The package can make decisions legible, but it cannot manufacture stronger evidence or guarantee the quality of execution that follows.

Review Rules

  • intelligence cannot make weak evidence strong by itself
  • downstream execution quality still depends on lab and runtime surfaces
  • recommendation quality is bounded by the transparency of its inputs and outputs

First Proof Check

  • packages/bijux-proteomics-intelligence/tests
  • src/bijux_proteomics_intelligence/policies.py and evaluators.py
  • src/bijux_proteomics_intelligence/report/ and outcomes.py

Design Pressure

The common drift is to treat a persuasive recommendation surface as if it were a substitute for evidence quality or downstream operational discipline.