Evidence map›Paper›PMID 42141031›Full record

ArticleNPJ digital medicine2026

Large language models require a new form of oversight: capability-based monitoring.

Katherine C Kellogg, Bingyang Ye, Yifan Hu, Guergana K Savova, Byron Wallace, Danielle S Bitterman

Abstract readLetter
In one paragraph

Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Katherine C KelloggMIT Sloan School of Management, Boston, MA, USA. kkellogg@mit.edu.
Bingyang YeAI in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.
Yifan HuHarvard John A. Paulson School Of Engineering And Applied Sciences, Cambridge, MA, USA.
Guergana K SavovaComputation Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Byron WallaceKhoury College of Computer Sciences, Northeastern University, Boston, MA, USA.
Danielle S BittermanAI in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA. dbitterman@bwh.harvard.edu.

Funding

Harvard Clinical and Translational Science CenterUM1TR004408 · NCATS · HARVARD MEDICAL SCHOOL · PI Lindsey Robert Baden, Lee Marshall Nadler · 2023 to 2026
$43.3M
Cancer Deep Phenotyping from Electronic Medical RecordsU24CA248010 · NCI · BOSTON CHILDREN'S HOSPITAL · PI HARRY S HOCHHEISER, GUERGANA K. SAVOVA · 2020 to 2026
$6.1M
Informatics strategies to improve immune-related adverse event detection in cancer patientsR01CA294033 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI Hugo Aerts · 2024 to 2026
$1.3M
American Cancer Society ACS.ASTRO-CSDG-24-1244514-01-CTPS.pc.gr.222210Division of Cancer Prevention, National Cancer Institute R01CA294033-01NCATS NIH HHS UM1TR004408NCI NIH HHS R01 CA294033NCI NIH HHS U24 CA248010NCI NIH HHS U24CA248010NCI NIH HHS U54CA274516-01A1Patient-Centered Outcomes Research Institute ME-2024C2-37484
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Identifiers

PMID42141031
PMCPMC13179377

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.