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Record W4313237436 · doi:10.1055/s-0042-1757908

A Blinded Comparative Study of Four Commercially Available LEDs and a Laser Light Curing Device

2022· article· en· W4313237436 on OpenAlexafffund
John C. Comisi, Cristiane Maucoski, Jonathan P. Beller, Kyle S. Dennis, Richard Bengt Price

Bibliographic record

VenueEuropean Journal of Dentistry · 2022
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsDalhousie University
FundersNational Center for Advancing Translational SciencesNational Institutes of HealthDalhousie UniversitySouth Carolina Clinical and Translational Research Institute, Medical University of South CarolinaMitacsCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsCuring (chemistry)Materials scienceLight-emitting diodeWhite lightDentistryLaserBiomedical engineeringComposite materialMedicineOpticsOptoelectronics

Abstract

fetched live from OpenAlex

OBJECTIVE: This study determined the effectiveness of five light-curing units (LCUs; four light-emitting diode [LED] and one laser) used on different settings to photo-activate four conventional resin-based composites (RBCs). MATERIALS AND METHODS: A total of 108 RBC specimens were photo-activated in a white Delrin mold representing a mesial-occlusal-distal (MOD) class II restoration in a molar tooth. The proximal boxes were 5 mm deep, and the mesial-distal length was 12 mm. Immediately after photo-curing, the RBC specimens were immersed in a solvent to remove the uncured materials, after which they were photographed and deidentified. A Research Electronic Data Capture survey was created using these images and sent to respondents who blindly assessed the ability of the various LCUs to photo-cure the MOD restorations. RESULTS: -test, Welch's one-way ANOVA, and Kruskal-Wallis rank test in the blinded survey data showed significant differences between the LED curing lights used for two 10-second cures and the laser curing light used for 1 second, and LED lights at lower settings. CONCLUSION: There was a significant difference in how the curing lights could photo-cure the RBCs used in this study. The laser curing light used for 1 second produced the worst results in all four RBCs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.095
GPT teacher head0.314
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2022
Admission routes2
Has abstractyes

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