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
10Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2330605480
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Kla Tantithamthavorn (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Productivity: 1 paper
Claim outcomes
- Other: 1 paper
- Developer Productivity: 1 paper
- Output Quality: 1 paper
- Task Completion Time: 1 paper
- Team Performance: 1 paper
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.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| Atlassian’s LLM-based code reviewer prompted code changes in nearly 39% of cases and was associated with a roughly 31% faster pull-request cycle and 36% fewer human review comments, suggesting substantial productivity gains from automation in developer workflows.arxiv | Kla Tantithamthavorn provider id |
2026-01-03 | 7 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 7 cumulative citations. This is a coverage summary, not an author score or h-index.