Field Gap

Under-studied area: Generalist AI hype

Over-represented in the literature

Demonstrations of fluent LLM/VLM output and single-benchmark scores

Under-represented

Rigorous measurement of hallucination rate, calibration, and failure modes on real neuro-oncology images

Why the gap exists

Fluency is easy to showcase; safety-relevant failure characterization is hard and less publishable

Open in the interactive atlas →

About this page

Curated and maintained by Resonant Labs. Reviewed by Claims are synthesized from the cited literature and graded per the Atlas methodology (about the Atlas). Last updated 2026-07-01.

This is an educational research resource from Resonant Labs, not clinical advice. Evidence grades and controversies are summarized from the literature and may change as the field evolves.