Mobility Opportunity Evidence Dossier — SAMPLE (synthetic data)

この成果物が扱う判断 The decision this addresses

何を決めようとしているか · What decision is being made?

1. 事実 · fact この地域の移動課題に資金を投じる根拠が十分か（合成データ） (the requester's own words)
2. 事実 · fact Geography stated by the requester: Sample City (synthetic) (customer-provided)
3. 事実 · fact User group stated by the requester: 75歳以上の住民 (customer-provided)
4. 事実 · fact Intended use stated by the requester: 議会向け予算説明 (customer-provided)

デューデリジェンスに値するもの What deserves diligence

どの課題・ギャップがデューデリジェンスに値するか · Which problems / solution gaps deserve further diligence?

1. 事実 · fact Gap SAMPLE-GAP-01 — REQUIREMENT_UNMET (OPEN, 2 unmet requirements) (concepts attached to a gap are PROPOSALS until validated)

現時点で分かっていること What is known

根拠のある事実は何か · What is supported by evidence?

1. 事実 · fact service change: "2026年4月に市内2路線が減便された（合成データ）" (1 passage · OFFICIAL)
   evidence SAMPLE-E01 · https://example.invalid/sample/service_change · observed 2026-05-01
2. 事実 · fact population: "75歳以上の住民は約1,200人（合成データ）" (1 passage · OFFICIAL)
   evidence SAMPLE-E02 · https://example.invalid/sample/population · observed 2026-05-02
3. 事実 · fact satisfaction: "60歳以上の約4割が便数に不満と回答（合成データ）" (1 passage · OFFICIAL)
   evidence SAMPLE-E03 · https://example.invalid/sample/satisfaction · observed 2026-04-20
4. 事実 · fact budget: "地域公共交通関連予算は前年度比横ばい（合成データ）" (1 passage · OFFICIAL)
   evidence SAMPLE-E04 · https://example.invalid/sample/budget · observed 2026-03-30

推論であるもの What is inference

どれが推論か · What is inference?

1. 事実 · fact Case SAMPLE-CASE-01 — サンプル市：路線減便後の高齢者の移動アクセス（合成データ） (state FOUNDER_REVIEW, version 1)
   evidence SAMPLE-E01, SAMPLE-E02, SAMPLE-E03, SAMPLE-E04 · https://example.invalid/sample/service_change · https://example.invalid/sample/population · https://example.invalid/sample/satisfaction · https://example.invalid/sample/budget · observed 2026-05-02
2. 推論 · inference 公開計画は運転手不足と減便を明記し、60歳以上の約4割が便数に不満と記載している（合成データ）。 (the Case thesis is an inference over the evidence, not a fact)
   evidence SAMPLE-E01, SAMPLE-E02, SAMPLE-E03, SAMPLE-E04 · https://example.invalid/sample/service_change · https://example.invalid/sample/population · https://example.invalid/sample/satisfaction · https://example.invalid/sample/budget · observed 2026-05-02
3. 推論 · inference 減便後も高齢者が週2回の通院移動を維持できること — for 75歳以上の住民（合成データ） (SOURCE_CLAIM · OPEN)
   evidence SAMPLE-E01, SAMPLE-E03

成熟度 Maturity

どの成熟度にあるか · What maturity exists?

1. 推論 · inference SOLUTION_CLASS demand-responsive-transport — INCLUDED (confidence 0.62)
   evidence SAMPLE-E01, SAMPLE-E03
2. 仮説 · hypothesis SOLUTION_CLASS volunteer-transport — REQUIRES_VALIDATION (confidence 0.35) (requires validation before it can be relied on)
   evidence SAMPLE-E02

分かっていないこと Unknowns

何が不完全か · What evidence is incomplete?

1. 不明 · unknown Missing evidence class: FUNDING_PATHWAY (named by the qualification engine)
2. 不明 · unknown Missing evidence class: OPERATOR_CAPACITY (named by the qualification engine)
3. 推奨 · recommendation Bounded research task FUNDING_PATHWAY: sample city DRT subsidy programme (OPEN) (public-source only; nobody is contacted)

実装・研究のギャップ Implementation or research gaps

どのギャップがあるか · Which implementation or research gaps exist?

1. 不明 · unknown Missing evidence class: FUNDING_PATHWAY (named by the qualification engine)
2. 不明 · unknown Missing evidence class: OPERATOR_CAPACITY (named by the qualification engine)
3. 推奨 · recommendation Bounded research task FUNDING_PATHWAY: sample city DRT subsidy programme (OPEN) (public-source only; nobody is contacted)

次の安全な一手 Next safe action

外部行動なしに進められる次の一手は何か · What is the next action that commits nothing externally?

INCOMPLETE — this section is written by the reviewer before release; the compiler does not invent recommendations