Evidence map›Paper›PMID 42230704›Full record

ArticleScientific reports2026

An automated cloud-based system for in-situ geotechnical site characterization using cone penetration test (CPT/CPTu).

Mohamed Ezzat Al-Atroush, Ezz El-Din Hemdan, Christopher Woyeya

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 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

3 authors.

Mohamed Ezzat Al-AtroushDepartment of Engineering Management, College of Engineering, Prince Sultan University, Riyadh, KSA, Saudi Arabia. mezzat@psu.edu.sa.
Ezz El-Din HemdanGEOTECH 2.0 Research Lab, Engineering College, Prince Sultan University, Riyadh, KSA, Saudi Arabia.
Christopher WoyeyaGEOTECH 2.0 Research Lab, Engineering College, Prince Sultan University, Riyadh, KSA, Saudi Arabia.

Funding

Prince Sultan University PSU-CE-TECH-135, 2023
6 · The paper itself

Abstract

The Cone Penetration Test (CPT) is one of the most reliable and efficient methods for in situ site characterization, assessing ground improvement, and evaluating the potential for liquefaction. Despite CPT's primary limitation being its inability to retrieve physical soil samples, its real-time data continuous geo-data presents a unique opportunity. With that in mind, manual interpretation of CPT data for soil behavior type (SBT

Indexed as

Automated soil characterizationCloud-based computational workflowComparative analysisCone penetration test (CPT)Machine learningMapCPTSoil behavior type (SBTn)

Identifiers

PMID42230704
PMCPMC13338442

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.