research-document RFR-AFDA3197

Create a shared benchmark and decision threshold: Color-Difference Metric Validation

RFR-AFDA3197 — Create a shared benchmark and decision threshold: Color-Difference Metric Validation

Research opportunity

Create a shared benchmark and decision threshold for the claims or recommendations in “Color-Difference Metric Validation.”

Background

The originating artifact is accepted by the repository publishing inventory with status “computational-stress-test-complete-ground-truth-study-pending.” Its Work completed section provides the immediate evidence boundary.

Evidence trace

  • Origin document: content/projects/itten-color-contrasts/experiment-report/EX-ITTEN-008-color-metric-validation.md
  • Section: Work completed
  • Specific assumption challenged: The source's treatment in “Work completed” is sufficiently supported for its intended scope.
  • Supporting evidence excerpt: “Three thousand fixed-seed random sRGB pairs were compared with Euclidean Lab and Oklab before and after a simple gamut-compression transform. Rank stability and relation to luminance difference were recorded.”
  • Reason this opportunity exists: How competing methods or implementations compare on a common corpus with explicit utility, safety, and cost thresholds.

Unknowns

  • How competing methods or implementations compare on a common corpus with explicit utility, safety, and cost thresholds.

Dependencies

Suggested REP and methodology

  • Suggested REP: REP-EX-ITTEN-008-BENCHMARK
  • Methodology: Curate representative cases, blind ground truth where possible, define baselines and uncertainty-aware metrics, and run reproducible benchmark evaluations.
  • Expected outputs: Versioned benchmark, baseline implementations, scoring harness, datasheet, and adoption decision rule.
  • Success criteria: Independent teams can reproduce scores and the benchmark discriminates meaningful quality differences without rewarding proxy gaming.
  • Recommended agent: research-engineering-agent
  • Estimated effort: Medium
  • Expected knowledge gained: How competing methods or implementations compare on a common corpus with explicit utility, safety, and cost thresholds.

Evaluation

Dimension Score (1–5)
Knowledge gain 4
Potential impact 4
Cross-project reuse 5
Scientific importance 5
Dependency cost 5
Implementation difficulty 3
Frontier score 392

Confidence in this opportunity: moderate. Status: Open.