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Retention of resin‐based pit and fissure sealants: a systematic review

2006· review· en· W2008898406 on OpenAlexaff
Michèle Muller‐Bolla, C Tardieu, Ana Míriam Velly, Constance Antomarchi

Bibliographic record

VenueCommunity Dentistry And Oral Epidemiology · 2006
Typereview
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineFissureDentistryOrthodonticsComposite material

Abstract

fetched live from OpenAlex

The aim of the present study was to perform a systematic review on the retention of resin-based sealants (RBSs) according to the material used and the clinical procedure. An electronic search in MEDLINE, EMBASE, Cochrane library and SCOPUS was completed by a hand search in conference proceedings. One hundred and twenty-four studies were identified, 31 of which were included. The retention rate of auto-polymerized and light-cured RBSs did not differ significantly. Light-cured RBSs had a significantly higher retention rate than fluoride-containing light-cured RBSs at 48 months (RR = 0.80, 95% CI: 0.72-0.89) and more. Concerning the clinical procedure, the scarcity of well-conducted studies made judgement difficult, except for the isolation stage. If using a rubber dam did not affect retention of auto-polymerized RBSs, it did for fluoride-containing light-cured RBSs (RR = 2.03, 95% CI: 1.51-2.73).

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)0.009
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.006
Bibliometrics0.0110.011
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.166
GPT teacher head0.420
Teacher spread0.255 · 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 designSystematic review
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

Citations115
Published2006
Admission routes1
Has abstractyes

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