Evidence map›Paper›PMID 41300810›Full record

ArticleGenes2025

Reaping the Fruits of LLM Pruning: Towards Small Language Models for Efficient Non-Coding Variant Effect Prediction.

Megha Hegde, Jean-Christophe Nebel, Farzana Rahman

Abstract read
In one paragraph

Article in Genes, 2025. 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

3 authors.

Megha HegdeSchool of Computer Science and Mathematics, Kingston University, London KT1 2EE, UK.ORCID 0009-0008-2523-4619
Jean-Christophe NebelHolmwood House, Grove Crescent, Kingston Upon Thames KT1 2EE, UK.ORCID 0000-0003-1812-5269
Farzana RahmanSchool of Computer Science and Mathematics, Kingston University, London KT1 2EE, UK.ORCID 0000-0002-4785-5845

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Genetic VariationGenomicsModels, GeneticNatural Language ProcessingHumansQuantitative Trait Locideep learninglarge language modelnon-coding DNAsmall language modelvariant effect prediction

Identifiers

PMID41300810
PMCPMC12652071

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.