Evidence map›Paper›PMID 40649619›Full record

ArticleMaterials (Basel, Switzerland)2025

Classification of the Cutting Surface Topography Using a Set of Uncorrelated Parameters with High Discriminative Ability.

Rafal Rozanski, Elzbieta Kawecka, Andrzej Perec

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Rafal RozanskiFaculty of Technology, Jacob of Paradies University, 66-400 Gorzów Wielkopolski, Poland.ORCID 0000-0003-0766-0901
Elzbieta KaweckaFaculty of Technology, Jacob of Paradies University, 66-400 Gorzów Wielkopolski, Poland.ORCID 0000-0001-8492-4275
Andrzej PerecFaculty of Technology, Jacob of Paradies University, 66-400 Gorzów Wielkopolski, Poland.ORCID 0000-0003-3132-9514

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The paper proposes a new coefficient assessing the classification ability of parameters. In contrast to previously used indices, it does not require data normalization, examines the correlation between parameters with the highest classification ability, and determines, based on this, a complementary set that enables effective differentiation of surfaces that differ significantly. The empirical part is based on the values of 83 parameters that characterize the stereometric features of 22 surfaces created through different machining processes.

Indexed as

classification ability of parameterscuttinggeometric structure of the surfaceroughness

Identifiers

PMID40649619
PMCPMC12250832

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.