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 →
1Distinct papers
2Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5128189075
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Hiroyuki Uchida (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Inequality: 1 paper
- Innovation: 1 paper
- Productivity: 1 paper
Claim outcomes
- Research Productivity: 1 paper
- Ai Safety And Ethics: 1 paper
- Firm Revenue: 1 paper
- Output Quality: 1 paper
- Regulatory Compliance: 1 paper
- Task Completion Time: 1 paper
- Adoption Rate: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| When paired with mechanistic priors, synthesis‑aware design, robust external validation and regulatory alignment, AI can cut drug development time and raise early‑phase success rates; absent proper validation, dataset bias and misalignment with regulators can negate gains and create costly setbacks.openalex | Hiroyuki Uchida provider id |
2026-03-05 | 1 |
Citation observation summary
OpenAlex 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.