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Record W4206348368 · doi:10.53350/pjmhs2115123619

Success of Veneers with Indirect Resin Composite

2021· article· en· W4206348368 on OpenAlexaff
Amna Nazar, Muhammad Bader Munir, Aamir Rafiq, Saira Khalid, Hammad Hassan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDentistry
TopicDental Radiography and Imaging
Canadian institutionsCollège Montmorency
Fundersnot available
KeywordsDentistryResin compositeMedicineOrthodonticsDental restorationComposite numberMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Objective: To evaluate the success of veneers fabricated with indirect resin composite (Ceramage). Method: This Descriptive Case Series was completed at de’ Montmorency college of dentistry/Punjab Dental Hospital, Lahore over the period of 6 months from Jul 2018 to Jan 2019. Patients fulfilling the inclusion criteria of the study were selected. After the informed consent, pre-operative radiographs of the teeth to be veneered were taken to rule out any caries activity or periapical pathology. A total of 60 veneers were fabricated with indirect resin composite. Patients were followed up with 6 months interval and restorations were evaluated for complications like dislodgment, chipping, fracture, sensitivity and bleeding from gums. Results: Out of total of 60 veneers 50 were successful and 10 were unsuccessful. only 4 showed slight postoperative sensitivity,4 showed moderate postoperative sensitivity and 2 showed severe postoperative sensitivity.out of total 5 showed minor crack lines,3 showed minor chipping (1/4 of the restoration) and 2 showed moderate chipping (1/2 of restoration). Success rate of veneers fabricated with indirect resin composite (Ceramage) was 83.3%. Conclusions: The indirect veneers have undergone considerable improvement and refinement over the past few decades and have now matured into a predictable restorative concept in terms of longevity, periodontal response and patient satisfaction. The design of the restoration should take the material properties into account in order to enhance the clinical performance. Key words: Indirect Resin Composite, Veneers, Smile makeover

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations1
Published2021
Admission routes1
Has abstractyes

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