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Record W2422745727 · doi:10.21616/2414-2050.2016.02.6

Dental Management of Special Needs Patients: A Literature Review

2016· review· en· W2422745727 on OpenAlexvenueno aff
Etiene Andrade Munhoz

Bibliographic record

VenueGlobal Journal of Oral Science · 2016
Typereview
Languageen
FieldDentistry
TopicDental Anxiety and Anesthesia Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsDentistryMedicine

Abstract

fetched live from OpenAlex

The dental management of special needs patients creates doubt and anxiety among dentists. The theme is underexplored throughout the undergraduate course and the dentists have not enough theoretical foundation to work on this field. Special needs patients are those individuals who have permanent or transitory mental, physical, organic social and / or behavioral impairments. Thus, the aim of this study was to assist dentists in the best dental management choice for special needs patients. It was revised and more specifically detailed the management on dental base office, the management under sedation and under general anesthesia, and home care treatments for patients with special needs, with the aim of developing guidelines on management of dental patients with special health care needs to facilitate the execution of dental treatment of these patients. From this literature review, we proposed a guideline to assist the dentist in choosing the best therapeutic approach for the dental treatment of patients with special needs.

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)0.005
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.334
Teacher spread0.316 · 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

Citations16
Published2016
Admission routes1
Has abstractyes

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Same venueGlobal Journal of Oral ScienceSame topicDental Anxiety and Anesthesia TechniquesFrench-language works237,207