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Record W2410559467

Fixed orthodontic appliances in the management of severe dental trauma in mixed dentition: a case report.

2013· article· en· W2410559467 on OpenAlexaff
Fouad-Hassan Ebrahim, Gajanan Kulkarni

Bibliographic record

VenuePubMed · 2013
Typearticle
Languageen
FieldHealth Professions
TopicDental Trauma and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSplint (medicine)Tooth AvulsionMedicineIntrusionDental traumaAvulsionDentistryOrthodonticsDentitionSurgeryGeology
DOInot available

Abstract

fetched live from OpenAlex

We describe a case of complex trauma to the early mixed dentition in which tooth avulsion, intrusion, extrusion and lateral luxation were managed effectively using a fixed, non-rigid orthodontic splint after treatment with a traditional wire-composite splint had failed. The use of orthodontic brackets and flexible wires provided several advantages, such as the ability to splint severely malpositioned teeth; easy assessment without removing the splint; slow, gentle repositioning of traumatized teeth; and gradual reestablishment of the arch form allowing for ease of future prosthodontic rehabilitation. Therefore, orthodontic appliances should be considered as a viable option for managing complex dental trauma.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0080.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.085
GPT teacher head0.358
Teacher spread0.273 · 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 designCase report
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

Citations14
Published2013
Admission routes1
Has abstractyes

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