品質線——不叫人打分數也能量成果品質

研究問題

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?

主張

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.

限制

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.

關係

歷史與來源歷程

Canonical URL

https://evemisslab.com/ai/research/RES-2026-0102/

機器可讀

/ai/research/RES-2026-0102/index.json

快照

AI-SNAPSHOT-v0.1-fe85b9694a45

來源歷程

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