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Record W125180361

Quantitative measurement of tooth and ceramic wear: in vivo study.

2008· article· en· W125180361 on OpenAlexaff
Maged K. Etman, Mark Woolford, Stephen Dunne

Bibliographic record

VenuePubMed · 2008
Typearticle
Languageen
FieldDentistry
TopicDental Erosion and Treatment
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsProceraEnamel paintMaterials scienceDentistryCeramicSignificant differenceTooth wearOrthodonticsComposite materialMedicine
DOInot available

Abstract

fetched live from OpenAlex

PURPOSE: The aim of this study was to quantitatively measure tooth and ceramic wear over a 2-year period using a novel superimposition technique. Three ceramic systems--experimental hot-pressed ceramic (EC), Procera AllCeram (PA), and metal-ceramic--were used. MATERIALS AND METHODS: A total of 90 posterior crowns in 48 patients were randomized into 3 groups, and impressions were made at baseline and at 6-month intervals for 2 years. Clinical images were taken after using a dye to highlight surface changes. The impressions were digitized and modeled as superimposable 3-dimensional colored surface images. The depth of wear at the occlusal contact areas was quantitatively measured at 6, 12, 18, and 24 months. RESULTS: The quantitative evaluation showed more wear in Procera AllCeram at the occlusal contact areas, whereas the experimental and metal-ceramic systems showed less wear. There was a significant difference in the amount of enamel worn between all types of restorations (P < .05). There was a statistically significant difference (P < .05) in the mean depth of wear between all systems. CONCLUSIONS: The metal-ceramic and experimental systems showed less change, indicating improved wear resistance compared with Procera AllCeram. In addition, enamel opposing metal-ceramic and experimental crowns showed less wear compared to enamel opposed by Procera AIICeram crowns.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.081
GPT teacher head0.276
Teacher spread0.195 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations100
Published2008
Admission routes1
Has abstractyes

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