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
11Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2025. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2333610970
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- C. Lazik (semantic scholar, provider refresh)
- Christopher Lazik (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Decision Quality: 1 paper
- Research Productivity: 1 paper
- Skill Acquisition: 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 |
|---|---|---|---|
| Human-AI teams perform better when humans can learn from outcomes: experiments that provide outcome feedback—especially paired with AI explanations—show positive synergy, whereas explanations alone often harm joint performance.arxiv | C. Lazik provider id |
2025-12-15 | 4 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 4 cumulative citations. This is a coverage summary, not an author score or h-index.