Data & measurement
Normalize impact variables from heterogeneous raw measures to [0,1]. State targets v_i^target and level ceilings alongside every reported norm. Write explicit operational definitions for each symbol in your protocol, even when abbreviations look standard. Log instrument versions, sample frames, and cleaning rules whenever estimates are refreshed so longitudinal comparisons stay valid.
Solution & proof
Conceptual summary: When lower raw values mean better outcomes (e.g. Transmission Break Point), subtract from 1 so higher is always better. Treat this as a measurement recipe: map each symbol to an empirical quantity, substitute estimates, and simplify with ordinary algebra (including logarithms, min/max caps, or piecewise branches where shown). Where limits or integrals appear, approximate with discrete sums on cohorts or time steps when closed forms are impractical. Interpret the result against thresholds in the cited source and report uncertainty on inputs.
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Source & tags
Source
Impact measurement framework — Normalization Rules