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Record W4386438711 · doi:10.2217/fmb-2022-0203

Current Antibacterial Agents in Dental Bonding Systems: A Comprehensive Overview

2023· review· en· W4386438711 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

VenueFuture Microbiology · 2023
Typereview
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of SaskatchewanUniversity of Alberta
Fundersnot available
KeywordsBiofilmAntimicrobialOral cavityStreptococcus mutansDentistryAntibacterial agentDental restorationAntibacterial activityChemistryDental plaqueBacteriaMicrobiologyMedicineBiologyAntibiotics

Abstract

fetched live from OpenAlex

Dental caries is mainly caused by oral biofilm acid, and the most common dental restoration treatment is composite dental restorations. The main cause of failure is secondary caries adjacent to the restoration. Long-term survival of dental materials is improved by the presence of antibacterial agents, which selectively inhibit bacterial growth or survival. Chemical, natural and biomaterials have been studied for their antimicrobial activities and antibacterial bonding agents have been improved. Their usage has been increased to inhibit the growth of invading and residual bacteria in the oral cavity, as biofilm accumulation increases the risk of treatment failure. In this article, the success and applications of antibacterial agents are discussed in dental bonding systems.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.649
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.005

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 head0.112
GPT teacher head0.389
Teacher spread0.277 · 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