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Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review. How this is built →
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Hideki Nakamura

Provider-ID corpus identity

1Distinct papers
2Unique collaborators
1/1Semantic Scholar citation coverage

Publication span: 2026. Corpus fetch span: 2026.

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Identity provenance

Provider IDs

  • Semantic Scholar: 49705141

ORCID evidence

No valid ORCID is stored.

Observed aliases (1)
  • Hideki Nakamura (semantic scholar, provider refresh)

Topics and outcomes in this view

Assessment themes

  • Adoption: 1 paper
  • Productivity: 1 paper

Claim outcomes

Papers in the Semantic Scholar view

Latest stored Semantic Scholar author observations only. Citation counts below are from the same provider and are not combined with other services.

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Hideki Nakamura's distinct papers under the selected provider observation surface.
PaperAuthor evidenceDateProvider citations
A task-based CES framework lets researchers read automation from routine macro data; applying it to Japanese manufacturing reveals rising automation driven by capital deepening despite weak productivity gains.openalex Hideki Nakamura
provider id
2026-03-24 1

Citation observation summary

Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 1 cumulative citations. This is a coverage summary, not an author score or h-index.