Evidence map›Paper›PMID 39851783›Full record

ArticleBiomimetics (Basel, Switzerland)2025

Evaluation of Internal and Marginal Accuracy (Trueness and Precision) of Laminates Using DLP Printing and Milling Methods.

Mijun Noh, Habin Lee, Wansun Lee, Jaehong Kim, Jihwan Kim

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Mijun NohDepartment of Healthcare Sciences, Faculty of Dental Laboratory Science and Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea.ORCID 0000-0002-7440-5399
Habin LeeDepartment of Healthcare Sciences, Faculty of Dental Laboratory Science and Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea.
Wansun LeeDepartment of Dental Technology, Graduate School, Bucheon University, 25 56th Street, Bucheon 14632, Republic of Korea.
Jaehong KimDepartment of Dental Laboratory Science, College of Health Science, Catholic University of Pusan, 57 Oryundae-ro, Geumjeong-gu, Busan 46252, Republic of Korea.ORCID 0000-0002-2679-8802
Jihwan KimDepartment of Healthcare Sciences, Faculty of Dental Laboratory Science and Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea.ORCID 0000-0003-3889-2289

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study evaluated the internal and marginal accuracy (trueness and precision) of zirconia laminate veneers fabricated using the DLP printing and milling method, employing 3D analysis software program. The maxillary central incisor tooth of a typodont model was prepared by a dentist and scanned using a desktop scanner. An anatomical zirconia laminate was designed using computer-aided design (CAD) software and saved in a standard tessellation language (STL) format. Thirty zirconia laminates were manufactured using a milling machine (MLL group) and a DLP printer (PTL group). All the specimens were scanned, and their internal and marginal areas were edited accordingly. The root-mean-square value was used to assess the accuracy of the internal and marginal areas of the zirconia laminates. Statistical significance was evaluated using the Mann-Whitney U test. Statistically significant differences were found in RMS values for both groups in the internal and marginal areas (

Indexed as

3D printingaccuracydigital light processinglaminatezirconia

Identifiers

PMID39851783
PMCPMC11761881

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.