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Record W2768202027 · doi:10.13034/jsst.v10i2.218

Nanodentistry: The benefits of nanotechnology in dentistry and its impact on oral health

2017· article· en· W2768202027 on OpenAlexvenueno aff
Peola Jayne Ellis

Bibliographic record

VenueJournal of Student Science and Technology · 2017
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsnot available
Fundersnot available
KeywordsMultidisciplinary approachOral healthDentistryNanotechnologyMedicinePolitical scienceMaterials science

Abstract

fetched live from OpenAlex

Nanotechnology is a multidisciplinary field that covers a variety of technological advancements. This branch of technology operates on objects that are less than one billionth of a meter which is equal to one nanometer, therefore focusing its job at the molecular and atomic level. The application of nanotechnology was primarily used in medicine however the emergence of nanodentistry has enabled dental technicians to modify various nanotechnologies to specify them to the field of dentistry. These advancements greatly impact the way dentists go about diagnosing patients, and in doing so using the proper material in order to improve patient treatment. Nanodentistry provides dentists with a new alternative approach that can be applied in their dental practice to treat oral health related problems with a higher degree of specificity.The applications of nanodentistry are designed to achieve maximum therapeutic efficacy with minimal side effects. There are several devices that are used to treat periodontal related illnesses, perform tissue regeneration and bone grafting. Some of these devices include: nanoparticles, nanoassemblers and nanocrystalline hydroxyapatite. These technological devices play an imperative role in helping dentists and dental technicians to analyze information and make precise judgments in the treatment of patients to improve their oralhealth and wellbeing while identifying ineffective current methods.La nanotechnologie est un domaine pluridisciplinaire qui couvre une variété de progrès technologiques. Cette division de la technologie règle des objets de moins d’un milliardième de mètre de largeur (égale à un nanomètre) et se concentre sur les niveaux moléculaires et atomiques. La nanotechnologie est principalement utilisée enmédecine, cependant, l’émergence de la nanodentisterie a permis aux techniciens dentaires de modifier diverses nanotechnologies pour les adapter au domaine de la dentisterie. Ces progrès ont un impact significatif sur la façon dont les dentistes diagnostiquent les patients et utilisent le matériel approprié pour améliorer le traitement des patients. La nanodentisterie fournit une nouvelle approche aux dentistes qui peut être appliquée dans la pratique dentaire pour traiter les problèmes de santé bucco-dentaire avec un degré plus élevé de précision. Les applications de nanodentisterie sont conçues pour atteindre une efficacité thérapeutique maximale tout en minimisant les effets secondaires. Il existe plusieurs dispositifs utilisés pour traiter les maladies parodontales eteffectuer la régénération tissulaire et la greffe osseuse. Certains de ces dispositifs incluent les nanoparticules, les nanoassembleurs et la hydroxyapatite nanocristalline. Ces dispositifs technologiques jouent un rôle impératif en aidant les dentistes et les techniciens dentaires à analyser l’information et à faire des jugements précis lors du traitement des patients. Ils peuvent améliorer la santé bucco dentaire et le bien-être des patients tout en identifiant les méthodes courantes inefficaces.

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)0.002
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.004
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.002

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 head0.020
GPT teacher head0.329
Teacher spread0.309 · 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
Published2017
Admission routes1
Has abstractyes

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