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Record W4409651702 · doi:10.1111/cid.70040

Selection of Cement Materials and Isolation Techniques for the Effective Removal of Residual Cement in the Cementation

2025· article· en· W4409651702 on OpenAlexvenueno aff
Süha Kuşçu, Yeliz Hayran

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2025
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
FundersGaziosmanpasa Üniversitesi
KeywordsCementCementation (geology)Materials scienceDentistryAbutmentCrown (dentistry)Dental cementComposite materialAdhesiveMedicineEngineeringStructural engineering

Abstract

fetched live from OpenAlex

AIM: This study aimed to investigate the impact of different cement and cement isolation techniques used in implant-supported restorations on eliminating residual cement. MATERIALS AND METHODS: This study employed two distinct cement isolation methods: rubber dam and polytetrafluoroethylene tape. The study comprised three primary groups comprising 30 samples, categorized based on the isolation methods and control group. The cement excess was removed with a dental explorer probe for the control group. Moreover, three different cement materials were used: polycarboxylate, temporary implant, and resin cement. Each primary group was subdivided into three subgroups according to the type of cement used, leading to 10 samples per subgroup. Cobalt-chromium superstructures, intended to be cemented onto the implant analog-abutment complex, were fabricated using the direct metal laser sintering method. The crowns were filled with cement, and after the cementation process, any excess cement was subsequently removed using the designated isolation method. After removal, images of the cement residues at the gingival margin of the crown-abutment complex and occlusal surface of the gingiva around the implant were captured. These images were then analyzed using Adobe Photoshop CC2018, wherein excess cement was marked using the Lasso Tool to quantify the total area. The excess cement data was analyzed using IBM SPSS Statistics Version 23 software. RESULTS: The results of the three-way ANOVA showed a difference in excess cement amounts between the isolation methods and cement materials (p < 0.001). In evaluating the isolation methods, the rubber dam was identified as the most suitable for temporary cement, while polytetrafluoroethylene tape was determined as the most suitable method for resin cement. Using a dental probe resulted in the highest amount of residual cement across all cement materials. Among the cement types, polycarboxylate cement exhibited the highest residual cement amount, followed by temporary implant cement and resin cement. CONCLUSIONS: The amount of excess cement was influenced by the isolation method and the type of cement used. The rubber dam emerged as the most effective method for minimizing cement residues. The most significant amount of residual cement was identified for polycarboxylate, whereas the lowest amount was observed for resin cement. The appropriate isolation method should be selected based on the type of cement.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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

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 head0.089
GPT teacher head0.490
Teacher spread0.401 · 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 designBench or experimental
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

Citations5
Published2025
Admission routes1
Has abstractyes

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