research-document RFR-D98B4DC4

Create a shared benchmark and decision threshold: Atlas Perceptual Measurement Layer

RFR-D98B4DC4 — Create a shared benchmark and decision threshold: Atlas Perceptual Measurement Layer

Research opportunity

Create a shared benchmark and decision threshold for the claims or recommendations in “Atlas Perceptual Measurement Layer.”

Background

The originating artifact is accepted by the repository publishing inventory with status “Proposed Canonical Foundation.” Its Architecture section provides the immediate evidence boundary.

Evidence trace

  • Origin document: content/projects/project-atlas/research-note/df-atlas-color-005-perceptual-measurement-layer.md
  • Section: Architecture
  • Specific assumption challenged: The source's treatment in “Architecture” is sufficiently supported for its intended scope.
  • Supporting evidence excerpt: “text ┌──────────────────────────────────────────────────────┐ │ 1. Source Record │ │ spectrum, XYZ, measured Lab, encoded RGB, material │ └──────────────────────────┬───────────────────────────┘ ↓ ┌──────────────────────────────────────────────────────┐ │ 2. Physical / Colorimetric Normalization │ │ illuminant, observ…”
  • 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-ATLAS-PERCEPTUAL-MEASUREMENT-LAY-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.