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Record W2100916134 · doi:10.2341/11-086-l

Effect of Composite Insertion Technique on Cuspal Deflection Using an In Vitro Simulation Model

2012· article· en· W2100916134 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

VenueOperative Dentistry · 2012
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsShrinkageComposite numberMaterials scienceComposite materialDeflection (physics)AdhesiveResin compositeDentistryOpticsMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to investigate, by simulation, the effect of conventional composite resin insertion techniques on cuspal deflection using bonded typodont artificial teeth. The deflection produced by a new low-shrinkage composite was also determined. MATERIALS AND METHODS: Sixty standardized MOD preparations on ivorine maxillary premolars were prepared: group A at 4 mm depth and group B at 6 mm depth. Each group was further subdivided according to composite insertion technique (n=6), as follows: 1) bulk insertion, 2) horizontal increments, 3) tangential increments, and 4) a modified tangential technique. Preparations were microetched, acid-cleaned, and bonded with adhesive resin to provide micromechanical attachment before restoration with a conventional composite (Spectrum TPH( 3 ), Dentsply). Two additional subgroups at 4 mm and 6 mm depth (n=6) were restored in bulk using low-shrinkage composite (Filtek LS, 3M/ESPE). All groups received the same total photo-polymerization time. Cuspal deflection was measured during the restorative procedure using two Linear Variable Differential Transformers attached to a data acquisition system. RESULTS: The average cuspal deflections for group A were 1) 40.17 ± 1.18 μm, 2) 25.80 ± 4.98 μm, 3) 28.27 ± 5.12 μm, and 4) 27.33 ± 2.42 μm. The deflections in group B were 1) 38.82 ± 3.64 μm, 2) 50.39 ± 9.17 μm, 3) 55.62 ± 8.16 μm, and 4) 49.61 ± 8.01 μm. Cuspal flexure for the low-shrinkage composite was 11.14 ± 1.67 μm (group A: 4 mm depth) and 16.53 ± 2.79 μm (group B: 6 mm depth). CONCLUSIONS: All insertion techniques using conventional composite caused cuspal deformation. In general, deeper preparations showed increased cuspal deflection-except in the case of bulk insertion, which was likely affected by decreased depth of cure. Cuspal movement using low-shrinkage composite was significantly reduced.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.539

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 communication0.0000.001
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 head0.038
GPT teacher head0.384
Teacher spread0.347 · 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