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
3Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2025. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5116124539
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Rapeepat Klangbunrueang (openalex, provider refresh)
- Rapeepat Klangbunrueang (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Innovation: 1 paper
Claim outcomes
- Other: 1 paper
- Output Quality: 1 paper
- Market Structure: 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 |
|---|---|---|---|
| Deep-learning models, led by GRUs, forecast a simulated Thai ESG stock index substantially better than classical ARIMA-style approaches over a 36-day horizon. The advantage endures even with limited historical data, implying advanced AI can strengthen ESG market signals in data-constrained emerging markets.openalex | Rapeepat Klangbunrueang provider id |
2025-12-22 | 3 |
Citation observation summary
OpenAlex supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 3 cumulative citations. This is a coverage summary, not an author score or h-index.