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. Editorial lead: Claims are synthesized from the cited literature and graded per the Atlas methodology (about the Atlas). Page generated 2026-10-02. This is not a new clinical review date.

This is an educational research resource from Resonant Labs, not clinical advice. Atlas assessments are heuristic, not probabilities or formal GRADE ratings. Findings are summarized from the literature and may change as the field evolves.