research-document RFR-B1D83585

Create a shared benchmark and decision threshold: Project Atlas Autonomous Research Report: Johannes Itten's Seven Color Contrasts

RFR-B1D83585 — Create a shared benchmark and decision threshold: Project Atlas Autonomous Research Report: Johannes Itten's Seven Color Contrasts

Research opportunity

Create a shared benchmark and decision threshold for the claims or recommendations in “Project Atlas Autonomous Research Report: Johannes Itten's Seven Color Contrasts.”

Background

The originating artifact is accepted by the repository publishing inventory with status “Research Synthesis.” Its Model 1 — Contrast Vector Model section provides the immediate evidence boundary.

Evidence trace

  • Origin document: content/projects/project-atlas/research-report/project-atlas-autonomous-research-itten-seven-contrasts-v0-1.md
  • Section: Model 1 — Contrast Vector Model
  • Specific assumption challenged: The source's treatment in “Model 1 — Contrast Vector Model” is sufficiently supported for its intended scope.
  • Supporting evidence excerpt: “text C = f( ΔL, ΔH, ΔC, A, B, F, D, Ad, S, T ) Where: - ΔL = lightness or luminance difference - ΔH = chromatic-direction difference - ΔC = chroma, colorfulness, or saturation difference - A = area ratio - B = boundary structure - F = spatial frequency - D = surround distribution - Ad = adaptation - S = semantic diffe…”
  • 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-PROJECT-ATLAS-AUTONOMOUS-RESEARC-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.