Evidence map›Paper›PMID 42367881›Full record

ArticlebioRxiv : the preprint server for biology2026

Changchang Li, Abhilash Dhal, Kai Gravel-Pucillo, Kaelyn Long, Michele Waters, Ino de Bruijn, Sean Davis, Sehyun Oh

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Changchang LiInstitute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA.
Abhilash DhalIndependent Researcher, India.
Kai Gravel-PucilloInstitute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA.
Kaelyn LongInstitute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA.
Michele WatersMemorial Sloan Kettering Cancer Center, New York, NY, USA.
Ino de BruijnMemorial Sloan Kettering Cancer Center, New York, NY, USA.
Sean DavisDepartments of Biomedical Informatics and Medicine, University of Colorado Anschutz School of Medicine, Denver, Colorado, USA.
Sehyun OhInstitute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA.ORCID 0000-0002-9490-3061

Funding

Cancer Genomics: Integrative and Scalable Solutions in R/BioconductorU24CA289073 · NCI · GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY · PI Sean Davis, Levi Waldron · 2024 to 2026
$3.2M
NCI NIH HHS U24 CA289073
6 · The paper itself

Abstract

Public biomedical repositories hold substantial reuse potential, but inconsistent metadata routinely blocks integration across studies. Recent LLM-based harmonization approaches address scale but suffer from non-determinism, hallucinated ontology terms, and, in their highest-accuracy configurations, dependence on proprietary APIs or labeled fine-tuning data. A more fundamental concern is that LLM accuracies on widely-used public benchmarks may substantially inflate transferable capability: under a contamination-controlled evaluation protocol we developed, the apparent LLM-only advantage on the GDC schema-mapping benchmark is inverted and three out of five LLMs recovers 80-100% of GDC identifiers from zero-schema context, suggesting direct memorization. Building on this insight, we present

Identifiers

PMID42367881
PMCPMC13308024

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.