SRC06-E01 — Deep Research Agents: Incremental Progress¶
Description¶
Academic evaluation of deep research agents concludes they represent incremental progress with significant citation accuracy problems and lack of analytical rigor.
URL¶
https://www.jmir.org/2026/1/e88195
Extract¶
Deep research agents represent incremental evolution rather than paradigm shift. Citation accuracy: OpenAI best (~95% identifiable, ~70% correct), Google/Perplexity frequently produce fabricated citations (47-50% fake authors/titles). Medical trainees should avoid leaning too heavily on AI-prepared syntheses. Agents should be embraced as assistive tools rather than pseudoexperts. Realizing potential requires transparent retrieval architectures, robust benchmarking, and explicit educational integration.
Relevance to Hypotheses¶
| Hypothesis | Relevance | Strength |
|---|---|---|
| H1 — Comprehensive frameworks | Contradicts (even leading tools lack rigor) | Strong |
| H3 — Partial features | Supports (citation transparency partial, analytical rigor absent) | Strong |
Context¶
FACT: Published 5 days before this research run (2026-03-26). FACT: Peer-reviewed in JMIR. JUDGMENT: The most current academic assessment confirms that deep research agents prioritize information gathering over analytical rigor, validating the Q003 finding that no tool implements comprehensive analytical frameworks.