Evidence map›Paper›PMID 42452075›Full record

ArticlePolymers2026

Predicting Interfacial Pull-Out Performance of Nano-B

Havva Esra Bakbak, Aytuğ Onan, Erman Bilisik, Kadir Bilisik

Abstract read
In one paragraph

Article in Polymers, 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

4 authors.

Havva Esra BakbakDepartment of Electrical and Electronic Engineering, Ege University, Izmir 35040, Turkey.ORCID 0000-0001-5432-6944
Aytuğ OnanDepartment of Computer Engineering, Izmir Institute of Technology, Izmir 35430, Turkey.ORCID 0000-0002-9434-5880
Erman BilisikNanotechnology Application and Research Centre (ERNAM), Erciyes University, Kayseri 38039, Turkey.
Kadir BilisikNanotechnology Application and Research Centre (ERNAM), Erciyes University, Kayseri 38039, Turkey.ORCID 0000-0002-0592-980X

Funding

Erciyes University FDK-2023-13113
6 · The paper itself

Abstract

Interfacial yarn pull-out plays a critical role in load transfer and energy dissipation in soft ballistic materials; however, its multistage and friction-dominated nature makes comprehensive experimental characterization time-consuming and experimentally demanding. In this study, a stage-wise physics-guided machine learning (PG-HML) framework is proposed to predict the pull-out behavior of nano hexagonal boron carbide (nh-B

Indexed as

aramid fibermachine learningnano hexagonal boron carbide (nh-B4C)pull-out forceshear

Identifiers

PMID42452075
PMCPMC13363964

What OpenQuestion holds

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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.