Supplemental field-trial laboratory

When the average hides a rare failure

A deterministic, prediction-first bench. Every control has units; every result has an inspectable table and static account.

Prediction

At five percent code prevalence, which candidate will prevalence-weighted mean risk select, and which candidate will worst-environment risk select? Explain why before revealing the bench.

Worst-environment risk ignores prevalence; a weighted mean can prefer the fragile subset below the crossover.

Which candidate will the mean objective select at five percent code prevalence?

Practice only · this interaction never becomes mastery evidence.

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Rare room discounted

The frequency-first candidate's large code loss is multiplied by a small prevalence, so its weighted mean remains lower even though its worst-room loss is 0.84.

code prevalence
5%
fragile mean
0.1294
mean selects
Frequency-first
robust mean
0.1579
worst selects
Robust capacity

Mean-risk crossover

At the crossover the candidates have the same prevalence-weighted mean risk. Their worst-environment risks remain 0.84 and 0.27.

code prevalence
9.5238%
mean risk
0.163238
mean selects
Tie
worst selects
Robust capacity

Rare room carries enough weight

Once code receives enough prevalence, its large frequency-first loss outweighs that candidate's small advantage in common environments.

code prevalence
15%
fragile mean
0.2042
mean selects
Robust capacity
robust mean
0.1697
worst selects
Robust capacity

Concept anchors

The scenario connects scale, evidence, and model evaluation.

The lab is attached to concepts through explicit APPLIES relations. It does not alter their lesson containment or claim review state.

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Move between intuition and evidence.

Ephemerent News tells the result as an intuitive argument. Ephemerent Research preserves the paper, review, files, and version history. Atlas keeps this conceptual scenario available for sustained manipulation.