ResearchRES-2026-0102v0.1
Quality line — measuring outcome quality without asking humans for a score
Papers 06–08. Quality is a relation Q(Y | task, specification, environment, boundary), not a number an artifact carries: formalize what can be formalized (proof checkers, compilers, constraint solvers), structure what can be structured (requirement coverage, contradiction graphs, evidence checks, hard gates), and only then hand the genuine residual to humans — as many local binary or pairwise judgments reconstructed into a latent quality vector by a psychometric model (IBQF / BRQM), inside a typed, versioned, context-aware quality ontology for text, image, music, story and design.
Research questions
research_questions- Which parts of 'quality' can be decided by a formal system, which by structured checks, and which only by human perception?
- When humans must judge, what should they be asked so that they observe and the measurement system builds the scale?
- For high-ambiguity artifacts, which constructs must be defined before any item is written — and how does the ontology grow without moving the goalposts?
Claims
claims- Quality is not an intrinsic scalar; a scalar Q* exists only under a declared projection rule, task, weights, gates and boundary.
- Compile success ≠ correct program; all tests passed ≠ universal correctness; formal proof ≠ real-world goal correctness — specification and verification are separate axes.
- Binary observation ≠ binary phenomenon: {0,1}^N answers can reconstruct a continuous, multidimensional latent quality, and the binary-burden advantage is an empirical hypothesis (F3), not a law.
- Disagreement ≠ error; mean preference ≠ preference structure; reliability ≠ validity; novelty ≠ creativity.
Limitations
limitations- No experiment on this line has run (Experiment B is declared only); the EveMissLab IBQF/FDCS sources it builds on are internal theory.
- Paper 07 explicitly does not propose a clinical scale; the pain example illustrates observer burden only.
Relations
| Source | Relation | Target | Status | ID |
|---|---|---|---|---|
RES-2026-0102 Quality line — measuring outcome quality without asking humans for a score | belongs_to | PRG-2026-0101 Intelligence Physical Metrology (IPM) | ACTIVE | REL-2026-0354 |
RES-2026-0102 Quality line — measuring outcome quality without asking humans for a score | develops | THY-2026-0106 Structured quality, hard gates and the specification–verification separation | ACTIVE | REL-2026-0363 |
RES-2026-0102 Quality line — measuring outcome quality without asking humans for a score | develops | THY-2026-0107 Binary residual quality measurement (IBQF / BRQM) | ACTIVE | REL-2026-0364 |
RES-2026-0102 Quality line — measuring outcome quality without asking humans for a score | develops | THY-2026-0108 Typed, versioned quality ontology for high-ambiguity artifacts | ACTIVE | REL-2026-0365 |
RES-2026-0103 Capability line — how much intelligence remains without the loop, and the unified intelligence event | extends | RES-2026-0102 Quality line — measuring outcome quality without asking humans for a score | ACTIVE | REL-2026-0357 |
CLM-2026-0103 F3 — Binary burden hypothesis | belongs_to | RES-2026-0102 Quality line — measuring outcome quality without asking humans for a score | ACTIVE | REL-2026-0384 |
PAP-2026-0106 Paper 06 — How should output quality be measured? From formal correctness to structured intelligence quality | reports | RES-2026-0102 Quality line — measuring outcome quality without asking humans for a score | ACTIVE | REL-2026-0411 |
PAP-2026-0107 Paper 07 — Do not ask humans to numerically score their own feelings: IBQF binary measurement and low-burden quality evaluation | reports | RES-2026-0102 Quality line — measuring outcome quality without asking humans for a score | ACTIVE | REL-2026-0415 |
PAP-2026-0108 Paper 08 — How can natural language, images, and creative outputs be measured? A structured quality space for high-ambiguity artifacts | reports | RES-2026-0102 Quality line — measuring outcome quality without asking humans for a score | ACTIVE | REL-2026-0419 |
PAP-2026-0111 IPM v0.1 canonical index — series overview, unified notation and the v0.2 experimental entry point | reports | RES-2026-0102 Quality line — measuring outcome quality without asking humans for a score | ACTIVE | REL-2026-0432 |
History and provenance
- Canonical URL
- https://evemisslab.com/ai/research/RES-2026-0102/
- Machine-readable
/ai/research/RES-2026-0102/index.json- Snapshot
AI-SNAPSHOT-v0.1-fe85b9694a45- Provenance
source- EveMissLab research collection: Intelligence Physical Metrology (真本體論13)
extracted_by- Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports
extracted_at- 2026-09-11
generator- tools/extract_all.py
claim_boundary- status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports