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Record W4382182640 · doi:10.1002/cap.10255

Management of cervical external root resorption following connective tissue grafting

2023· article· en· W4382182640 on OpenAlexaff
Émilie Thibault, Suraya Dhalla, Douglas Deporter

Bibliographic record

VenueClinical Advances in Periodontics · 2023
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineDentistryResorptionConnective tissueSoft tissueGranulation tissueGingival recessionRoot resorptionGraftingSurgeryWound healingPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Cervical external root resorption (CERR) is not a common occurrence, but can result in a hopeless tooth prognosis. Its etiology is poorly understood and its management can be challenging. The present case report describes the late presentation and management of CERR at both maxillary first premolar teeth following connective tissue grafting (CTG) procedures including use of citric acid as a chemical root surface conditioner. METHODS AND RESULTS: A 55-year-old female was diagnosed with bilateral external cervical root resorption of both maxillary first premolar teeth 28 years after CTG procedures that had included the use of citric acid root conditioning. As both teeth were asymptomatic, the patient opted for repair of the lesions via full-thickness flap elevation, meticulous removal of all granulation tissue, and restoration of the lesions with a resin-modified glass ionomer. A 2-year follow-up has been completed with no significant complications to report. CONCLUSIONS: CERR usually develops asymptomatically and is found by chance in radiographs. Its etiology is unclear, but may appear some years after soft tissue grafting to manage gingival recession. Early detection is key to be able to repair the lesions with minimal intervention.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.167
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.042
GPT teacher head0.417
Teacher spread0.375 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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