Metric System Index
Metric System Index
EURE
EURE
EURE measures whether a corpus segment produces high entropy while also carrying strong unique-token behavior and low repetition pressure.
EURE measures whether a corpus segment produces high entropy while also carrying strong unique-token behavior and low repetition pressure.
Efficient complexity: rewards useful variation and entropy strength after repetition pressure is accounted for.
Efficient complexity: rewards useful variation and entropy strength after repetition pressure is accounted for.
Formula
Formula
Mean: average of entropy, unique-token score, and inverted Yule’s K. Balance: weakest component.
Mean: average of entropy, unique-token score, and inverted Yule’s K. Balance: weakest component.
Signals: Shannon entropy, unique-token behavior, and repetition control.
Signals: Shannon entropy, unique-token behavior, and repetition control.
What It Means
What It Means
EURE tests efficient complexity. It asks whether complexity is being produced without leaning on repetition or narrow vocabulary cycling.
EURE tests efficient complexity. It asks whether complexity is being produced without leaning on repetition or narrow vocabulary cycling.
Scoring Context
Scoring Context
Scores are standardized within the declared comparison pool, tokenizer, transform, and slice-size run before index calculation. Index values are therefore run-context-specific and should not be interpreted outside the stated configuration.
Scores are standardized within the declared comparison pool, tokenizer, transform, and slice-size run before index calculation. Index values are therefore run-context-specific and should not be interpreted outside the stated configuration.
Evidence Boundary
Evidence Boundary
The public EURE page describes aggregate metric behavior. It does not publish protected corpus text, third-party lyrics, artist names, album titles, song titles, or source-reconstructable mappings.
This page supports a metric-specific aggregate claim: EURE can show whether efficient complexity appears across entropy, unique-token behavior, and repetition control at the same time. It does not publish source text, identify protected reference material, or prove universal artistic ranking. The public result is strongest inside the tested comparison pool, and deeper source-level verification belongs in controlled review.
The public EURE page describes aggregate metric behavior. It does not publish protected corpus text, third-party lyrics, artist names, album titles, song titles, or source-reconstructable mappings.
This page supports a metric-specific aggregate claim: EURE can show whether efficient complexity appears across entropy, unique-token behavior, and repetition control at the same time. It does not publish source text, identify protected reference material, or prove universal artistic ranking. The public result is strongest inside the tested comparison pool, and deeper source-level verification belongs in controlled review.
Evidence Charts
Evidence Charts
Start with the EURE leaderboard to see the direct index ranking. Then use the slice-size trend to check whether the result holds across measurement windows.
Start with the EURE leaderboard to see the direct index ranking. Then use the slice-size trend to check whether the result holds across measurement windows.
EURE leaderboard
EURE leaderboard
Ranks the tested segments by EURE, the efficient-complexity lens.
Ranks the tested segments by EURE, the efficient-complexity lens.
EURE slice-size trend across top segments
EURE slice-size trend across top segments
Tracks EURE across slice sizes for the top segments.
Tracks EURE across slice sizes for the top segments.
EURE / LDI / RACS leaderboard comparison
EURE / LDI / RACS leaderboard comparison
Compares EURE, LDI, and RACS without merging the three lenses.
Compares EURE, LDI, and RACS without merging the three lenses.
Reference Comparison Boundary
Reference comparisons are baseline coordinates for interpreting metric behavior. They are not presented as artistic rankings or claims of superiority over other writers.