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Record W7051894960

A prevalência do uso do fio dentário na dentição decídua: revisão sistemática e meta-análise

2021· dissertation· pt· W7051894960 on OpenAlexaboutno aff

Bibliographic record

VenueRepositorio Institucional (Universidade Fernando Pessoa) · 2021
Typedissertation
Languagept
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Scope (computer science)Balance (ability)Randomized controlled trial
DOInot available

Abstract

fetched live from OpenAlex

Esta revisão sistemática teve como objetivo avaliar a prevalência do uso do fio dentário na dentição decídua. A pesquisa sistemática em seis bases de dados, B-on, Cochrane Library, PubMed, SciELO, Science Direct e Web of Science, permitiu encontrar 2333 artigos, que após seleção resultou na inclusão de 7 estudos observacionais que avaliaram a prevalência do uso do fio dentário em crianças até 6 anos de idade. A avaliação de risco de viés foi realizada utilizando a ferramenta Newcastle-Ottawa, mostrando que todos os artigos apresentaram boa qualidade. Seis dos sete estudos mostraram que mais de 70% das crianças nunca utilizam fio dentário. A meta-análise mostrou uma prevalência de uso de fio dentário de apenas 12,60% (IC95%: 7,69%-18,52%), a partir de estudos com elevada heterogeneidade de resultados (I2=94,75%; IC95%: 91,44%-96,78%). A forma de avaliação de utilização de fio dentário (sim/não) ou diário versus outras opções deverá ser alvo de homogeneidade em futuros estudos.

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)0.047
metaresearch head score (Gemma)0.130
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.130
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0120.035
Bibliometrics0.0150.014
Science and technology studies0.0010.001
Scholarly communication0.0070.004
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.022
GPT teacher head0.269
Teacher spread0.247 · 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 designMeta-analysis
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

Citations0
Published2021
Admission routes1
Has abstractyes

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