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Record W4386933564 · doi:10.3390/dj11090225

Retrospective Clinical Evaluation of RMGIC/GIC Class V Restorations

2023· article· en· W4386933564 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDentistry Journal · 2023
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsWestern University
Fundersnot available
KeywordsGlass ionomer cementDentistryMedicineStatistical significanceRetrospective cohort studyExact testInternal medicine

Abstract

fetched live from OpenAlex

The aim of this retrospective study was to evaluate the clinical performance of glass-ionomer cement (GIC) and resin-modified glass-ionomer cement (RMGIC) materials in Class V carious cervical lesions restored by dental students. Ninety-six (96) restorations performed with either GIC (Fuji IX) (n = 39) or RMGIC (Fuji II LC) (n = 57) were evaluated using the modified USPHS criteria by two independent investigators at two follow-up evaluations (two years apart). The Fisher statistical test was used to compare USPHS criteria and examine significant differences, with a significance level set at p < 0.05. The Kaplan-Meier algorithm was used to calculate the survival probability. The overall success rate of Class V restorations was 72.9% at the second follow-up evaluation, with restorations ranging in age from 2.5 to 3.5 years. The RMGIC (Fuji II LC) restorations exhibited a significantly higher overall success rate compared to the GIC (Fuji IX) restorations (p = 0.0104). Significant differences were observed in retention (p = 0.0034) and color match (p = 0.0023).

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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)0.0010.001

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 head0.127
GPT teacher head0.435
Teacher spread0.308 · 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