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Record W1549234891 · doi:10.21726/rsbo.v10i1.891

Lack of pulp sensitivity in maxillary canines submitted to orthodontic traction: a retrospective clinical study

2014· article· en· W1549234891 on OpenAlexaff
Luciana Louzada Ferreira, Eduardo Macluf Filho, Cláudio Luis Rodrigues, Carlos Eduardo da Silveira Bueno, Rodrigo Sanches Cunha

Bibliographic record

VenueRSBO · 2014
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineDentistryTraction (geology)OrthodonticsEngineering

Abstract

fetched live from OpenAlex

Orthodontic movement may cause a great number of tissue alterations in the dental pulp. However, these changes may not be entirely recognized owing to the difficulty in simulating clinical situations. Objective: The aim of this study was to clinically assess the incidence of negative pulp sensitivity to cold among maxillary canines in infraocclusion submitted to orthodontic traction. Material and methods: Two study groups were selected: an experimental group, comprising 32 canine teeth with complete root formation that had been submitted to orthodontic traction, and a control group, comprising 32 canine teeth with complete root formation that had never been submitted to any orthodontic movement. Results: Fourteen teeth from the experimental group showed lack of pulp sensitivity, whereas only one tooth from the control group showed negative pulp sensitivity. Fischer’s exact test revealed a significant difference between the groups (p < 0.05). Conclusion: In conclusion, the teeth that had been submitted to orthodontic traction were more likely to lack sensitivity than those that had not been submitted to the same procedure.

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 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.080
GPT teacher head0.394
Teacher spread0.315 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2014
Admission routes1
Has abstractyes

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