On MultiChallenge, initializing Mode 3 with a mismatched hand-designed expert graph yields an initial validation accuracy of only 54.0%. The self-evolution loop recovers through two phases: pruning mismatched transition edges (reducing edge count from 13 to 10 by Generation 5) and restructuring control flow, raising validation accuracy to 93.9% (approaching scratch-built Mode 5 at 94.9%).

On MultiChallenge, initializing Mode 3 with a mismatched hand-designed expert graph yields an initial validation accuracy of only 54.0%. The self-evolution loop recovers through two phases: pruning mismatched transition edges (reducing edge count from 13 to 10 by Generation 5) and restructuring control flow, raising validation accuracy to 93.9% (approaching scratch-built Mode 5 at 94.9%). · CiteArk

Measurement results

0/4 assessed

0 supported0 disputed or conflicting4 not assessed

The complete result group stays with its claim. Assessed rows come first; their judgments do not replace the whole-claim conclusion. Expand a row for conditions, sources, and evidence history.

Each row is a measurement with its reported value, latest available observation, and cumulative evidence state.
Metric and conditions	Reported	Latest observation	Evidence judgment
mode: Mode 3 · phase: initial	54%	—	Not assessed
mode: Mode 3 · generation: 5 · initialEdgeCount: 13	10 edges	—	Not assessed
mode: Mode 3 · phase: restructured	93.9%	—	Not assessed
mode: Mode 5 (scratch)	94.9%	—	Not assessed

Reported and observed measurements

Assessments (0)

Runs (0)

Measurement results