DGO Experiment 03 — Homogeneous Green / Evidence Root

Result: Controlled feasibility PASS
Date: 2026-09-16

作者： Neo.K
機構： EveMissLab／一言諾科技有限公司
版本： 原稿未標註（本次整理版）

Tested proposition

Multiple validators with different labels do not constitute independent validation when they share the same evidence root.

Core distinction:

Reviewer Count != Independent Evidence Count

Stage 0

The pipeline silently dropped one invalid source record.

Three validators independently reported PASS:

SchemaReviewer      PASS
UniquenessReviewer  PASS
QualityReviewer     PASS

But all three inspected the same evidence root:

normalized.csv

Observed counts:

distinct reviewer labels = 3
distinct evidence roots  = 1
rows seen by each reviewer = 1000

The traditional process therefore declared:

COMPLETE

A provenance/reconciliation perspective inspected the source boundary instead:

source rows    = 1001
imported rows  = 1000
rejected rows  = 0
accounted rows = 1000
missing IDs    = [1001]

Dynamic closure:

Homogeneous Reviewers      PASS
Provenance Reconciliation  FAIL
Completion                 INCOMPLETE

Stage 1

The repair did not force the invalid row into the normalized dataset.

Instead, it repaired provenance/accountability semantics by adding an explicit rejection ledger:

source rows    = 1001
imported rows  = 1000
rejected rows  = 1
accounted rows = 1001
missing IDs    = []

All three original validators remained PASS, while independent reconciliation changed to PASS.

Final:

Homogeneous Reviewers      PASS
Provenance Reconciliation  PASS
Completion                 COMPLETE

What this supports

This controlled case supports:

Agreement != Independence
Independent Evidence > Independent Labels
Evidence Root Count matters
Processed-View PASS != Source-Boundary Closure
NOT VISIBLE IN THE PROJECTION != NONEXISTENT

The important improvement did not come from adding a fourth reviewer over normalized.csv; it came from selecting a different evidence root.

Limitation

This is a synthetic ETL/accounting example designed to isolate evidence-root correlation. It does not establish a universal quantitative relationship between reviewer count and effective independence.