Purpose
The Apex scorecard turns the positive theory into a decision worksheet. It compares a candidate descendant or routing change against no-op and asks whether the proposal increases capability while preserving local privacy, human agency, useful diversity, and resource discipline.
Champion, challenger, specialist, no-op
Score the candidate as an ecology member, not only as a benchmark entry. All computation stays in this browser.
Interpretation
A positive score means the candidate deserves further evidence collection. It is not production approval. A negative score means no-op currently wins. The most important result is often not the number; it is the list of assumptions you need to measure.
FUNCTION apex_score(candidate, evidence)
benefit <- SUM(
evidence.delta_task_utility,
evidence.delta_human_capability,
evidence.delta_reuse,
evidence.delta_autonomy,
evidence.delta_local_privacy,
evidence.delta_efficiency,
evidence.delta_diversity
)
cost <- SUM(
evidence.delta_latency,
evidence.delta_memory,
evidence.delta_energy,
evidence.delta_maintenance
)
RETURN benefit - cost
END FUNCTIONSource reports used for this guide
These reports are preserved verbatim in the site archive. The guide above is an editorial synthesis and may narrow, qualify, or reorganize claims from the source material.