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Record W2549856502 · doi:10.14740/jcs304e

Midfacial Degloving Approach for Bilateral Giant Cell Reparative Granuloma

2016· article· en· W2549856502 on OpenAlexvenueno aff
Gaurav Ahluwalia, K. P. Morwani

Bibliographic record

VenueJournal of Current Surgery · 2016
Typearticle
Languageen
FieldDentistry
TopicOral and Maxillofacial Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDeglovingMaxillaFacial deformitySurgeryMandible (arthropod mouthpart)DeformityOtorhinolaryngologyDentistry

Abstract

fetched live from OpenAlex

Reparative giant cell granuloma is a rare benign tumor. Mandible is the most common site. The case is reported for its rarity in maxilla and difficulty in differentiating it from other giant cell lesions. Differentiation is only based on the clinical test and histopathological examination. Midfacial degloving approach popularized by Caisson et al and Conley in 1974 is best suited for bilateral facial lesions. This approach gives a wide exposure with no facial scar or deformity. The advantages of the degloving technique in exposure of the midface, maxilla, mandible, nasal cavities, and paranasal sinuses, have led to its increasing importance in the otorhinolaryngology. J Curr Surg. 2016;6(3-4):78-80 doi: https://doi.org/10.14740/jcs304e

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.064
GPT teacher head0.314
Teacher spread0.250 · 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 designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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