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Record W3203117577 · doi:10.1016/j.jmbbm.2021.104861

On the behaviour of zirconia-based dental materials: A review

2021· review· en· W3203117577 on OpenAlexafffund
Prashant Shelar, Hamidreza Abdolvand, Sheila Butler

Bibliographic record

VenueJournal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials · 2021
Typereview
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNarrative reviewCubic zirconiaComputer scienceClinical PracticeDentistryMaterials scienceMedicineComposite materialFamily medicine

Abstract

fetched live from OpenAlex

Zirconia-based dental materials are extensively used in clinical practice due to their tooth-like appearance, biofunctionality, biocompatibility, and affordability. However, premature clinical failures of veneering porcelains raise a concern about their integrity. Extensive studies have been performed over a decade to resolve this issue, but it is challenging to reference all information effectively. A single source identifying the significance of potential parameters on material performance has not previously been available. An evidence-based meta-narrative review technique was used to review the characteristic parameters that can affect the overall behaviour of zirconia-based materials. Keywords were chosen to assess manuscripts based on scientific coherence with this paper's research objective. Online keyword searches were carried out on ScienceDirect, PubMed, and SAGE databases for relevant published manuscripts from year 1985-2020.261 out of 3170 identified manuscripts were included. A total of 10 parameters were identified and classified into the material, manufacturing, and geometric aspects. The effect of every parameter was reviewed on the performance of the material. A discrepancy in findings was observed and is attributed to the fact that there is no standard methodology. This review acts as a single source that summarizes various parameters' contribution to zirconia-based dental materials' performance. This review facilitates manufacturing improvements by accounting for every parameter's effect on overall performance.

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)0.013
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.400
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.005
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0060.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0170.000

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 head0.046
GPT teacher head0.346
Teacher spread0.300 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreReview

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

Citations56
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materialsSame topicDental materials and restorationsFrench-language works237,207