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Record W4311053552 · doi:10.3390/curroncol29120740

Transoral Approach to Parotid Tumors: A Review of the Literature

2022· review· en· W4311053552 on OpenAlexvenueno aff
Giuseppe Riva, Andrea Lorenzi, Andrea Borello, Andrea Albera, Andrea Canale, Giancarlo Pecorari

Bibliographic record

VenueCurrent Oncology · 2022
Typereview
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsParapharyngeal spaceMedicineParotid glandNoveltyScarsRadiologySurgeryPathology

Abstract

fetched live from OpenAlex

Different surgical techniques have been proposed for parapharyngeal space tumors, including transcervical, transparotid, trans-mandibular, infratemporal, and transoral. The choice of the correct approach depends on the size, localization and nature of the tumor. The transoral approach can be used for benign prestyloid masses, such as tumors of the deep lobe of the parotid gland. It guarantees a short hospitalization without skin scars. The narrowed access represents the main limitation of this technique. This review will summarize and analyze the current knowledge about the transoral approach to parotid lesions. Thirty-seven studies were included in a qualitative and quantitative synthesis. The novelty of this review is the quantitative analyses of the clinical data reported in the included studies.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0080.008
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.223
GPT teacher head0.454
Teacher spread0.231 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations10
Published2022
Admission routes1
Has abstractyes

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