Admissibility-First Energy Measurement: Closure, Integrity, and Refusal-Coded Claims for Auditable Energy-System Results
Abstract
EA-1 (Admissibility-First Energy Measurement) is a measurement-governance instrument and reporting standard for energy-system claims (energy, power, efficiency/COP, heat rate, and related performance statements). It introduces an admissibility-first workflow: before interpreting results, EA-1 requires the claimant to declare a complete ClaimTuple (boundary, channels, window, thresholds, pipeline, uncertainty floor, and disclosures), then evaluates the submission through deterministic checks that prioritize closure, identifiability, and integrity. EA-1 outputs a replayable, auditable decision artifact rather than a narrative conclusion: a VerdictObject with one of three outcomes—PASS, REFUSE, or DOWNSCOPE—plus a ReceiptManifest and content-addressed hashes that make the result independently reconstructible. The standard distinguishes run-admissible execution (a valid evaluation occurred, including refusals) from publishable reporting (a citable outcome exists), and enforces conservative failure modes (e.g., insufficient data, not identifiable, integrity compromised, provenance failure). EA-1 also specifies permitted/prohibited output language to prevent overstated claims (e.g., “validated,” “debunked,” or mechanism assertions beyond the declared model family) and defines a required citation block that binds any public claim to verifiable run hashes, boundary/window declarations, and refusal or downscope operators. In short: EA-1 turns contested energy-performance claims into hash-bound, refusal-coded, audit-ready objects that can be reproduced, verified, and cited without relying on trust or informal interpretation. Suggested keywords: energy measurement, measurement & verification (M&V), metrology governance, reproducibility, audit trail, admissibility, boundary conditions, canonicalization, content-addressed receipts, refusal semantics, downscoping.
Fields of Study & Subjects
Scientific Measurement and Uncertainty Evaluation
Scientific Computing and Data Management
Building Energy and Comfort Optimization
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 15 February 2026
- Language
- EN