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
0Unique collaborators
1/1OpenAlex citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5123897772
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Geoffrey Ditta (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Org Design: 1 paper
- Productivity: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Organizational Efficiency: 1 paper
- Firm Productivity: 1 paper
- Error Rate: 1 paper
- Task Allocation: 1 paper
- Training Effectiveness: 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 |
|---|---|---|---|
| Simulations indicate AI-driven HR systems could have meaningfully boosted productivity and profitability in historical industrial firms, with the largest gains in labor‑intensive, hierarchical operations; results depend on modeling assumptions and do not replace causal evidence.semantic_scholar | Geoffrey Ditta provider id |
Fetched 2026-03-15 | 0 |
Citation observation summary
OpenAlex supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 0 cumulative citations. This is a coverage summary, not an author score or h-index.