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Record W3204274632 · doi:10.4322/978-65-995353-2-1.c70

ODONTOLOGIA BIOLÓGICA COMO PROPOSTA DE ATENDIMENTO EM SAÚDE BUCAL: UMA REVISÃO NARRATIVA

2021· book-chapter· pt· W3204274632 on OpenAlexaff
Franciele Celestino Bruno Pereira, Serena de Oliveira Guimarães, Jaqueline de Souza da Cruz Coelho, Tatiane Regina Costa Cezar, Adrielly Carvalho do Amaral, Michelle Miranda Lopes Falcão

Bibliographic record

VenueInstituto Produzir eBooks · 2021
Typebook-chapter
Languagept
FieldDentistry
TopicDental Radiography and Imaging
Canadian institutionsPrairie Improvement Network
Fundersnot available
KeywordsMedicineArt

Abstract

fetched live from OpenAlex

ResumoObjetivo Revisar a literatura sobre a proposta da odontologia biológica como estratégia de superação às limitações relacionadas ao serviço odontológico convencional no controle das doenças bucais.Método Foi realizada uma revisão da literatura nas bases PUBMED, Scielo e Google Schoolar sem restrição de idioma, tipo de estudo ou período através dos termos de busca odontologia, odontologia integrativa, odontologia biológica e Padrões de Prática Odontológica.Resultados A odontologia biológica surge no cenário da saúde bucal como uma proposta de atendimento odontológico que contempla o ajuste dos fatores internos e externos associados aos problemas bucais no plano de tratamento, correlacionando-os com possíveis desordens sistêmicas.Além disso, propõe o uso de insumos com menor nível de toxicidade orgânica atrelado à aplicação de técnicas menos invasivas e individualizadas.Associa elementos da medicina ocidental e oriental com vistas ao retorno do equilíbrio entre a mente, o corpo e o espírito.Considerações Finais A odontologia biológica revela-se como uma prática de saúde bucal que alinha prevenção e tratamento na busca da homeostase do indivíduo.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.010
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0040.006
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 head0.033
GPT teacher head0.280
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 designNot applicable
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".

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Citations0
Published2021
Admission routes1
Has abstractno

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