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Record W2762059646 · doi:10.1308/205016816819304213

The use of Intentional Replantation to Repair an External Cervical Resorptive Lesion not am Enable to Conventional Surgical Repair

2016· article· en· W2762059646 on OpenAlexaff
Kreena Pa Tel, Federico Foschi, Ioana Pop, Shanon Patel, Francesco Mannocci

Bibliographic record

VenuePrimary Dental Journal · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDental Trauma and Treatments
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsReplantationLesionMedicineTooth ReplantationDentistryRoot canalSurgeryRadiographyResorptionRoot resorptionPathology

Abstract

fetched live from OpenAlex

Intentional replantation consists of purposefully extracting a tooth, correcting the defect and replanting it into its original socket. This case report describes how this technique was used to successfully restore an external cervical resorptive (ECR) lesion. A 22-year-old man was diagnosed with ECR of the mandibular right canine following clinical and radiographic examination. CBCT showed the lesion had been initiated distally and extended circumferentially around the root canal. The nature of the resorptive lesion meant that it was inaccessible to repair conventionally in a predictable manner. This report describes how intentional replantation was used to access and restore the lesion with minimal patient cooperation and postoperative discomfort. At an 18-month recall the tooth was clinically sound with no radiographic evidence of inflammatory or replacement root resorption. Intentional replantation should be considered a viable treatment option when ECR is inaccessible and cannot be restored using conventional techniques.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.126
GPT teacher head0.405
Teacher spread0.279 · 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.

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

Citations9
Published2016
Admission routes1
Has abstractyes

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