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Record W3123319591 · doi:10.1002/hed.26606

A new landmark for lingual artery identification during transoral surgery: Anatomic‐radiologic study

2021· article· en· W3123319591 on OpenAlexaff
Tommaso Gualtieri, Vincenzo Verzeletti, Marco Ferrari, Pietro Perotti, Riccardo Morello, Stefano Taboni, Giovanni Palumbo, Marco Ravanelli, Vittorio Rampinelli, Davide Mattavelli, Alberto Paderno, Barbara Buffoli, Luigi Fabrizio Rodella, Piero Nicolai, Alberto Deganello

Bibliographic record

VenueHead & Neck · 2021
Typearticle
Languageen
FieldMedicine
TopicNasal Surgery and Airway Studies
Canadian institutionsSurgical Specialties (Canada)
FundersUniversità degli Studi di Brescia
KeywordsLandmarkMedicineAnatomical landmarkTransoral robotic surgeryTongueDissection (medical)Head and neckRadiologySurgeryArtificial intelligencePathologyComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: A landmark for the identification of the lingual artery (LA) through a transoral perspective can provide surgeons with an easy method to prevent and manage intraoperative bleeding during transoral approach to the base of tongue (BOT). METHODS: Thirteen tongue and five head and neck specimens were dissected to identify and assess the reliability of the lingual point (LP) as a new landmark for the LA at BOT. The pathway of 42 LAs was radiologically evaluated; axial depth and vertical offset were measured for each LA. RESULTS: Dissection study: a description of LP is provided; the LA was easily identified in all specimens (36/36 sides) using LP as a landmark. Radiologic study: the mean depth of the LA was 4.2 mm, the mean vertical offset was 1.3 mm. CONCLUSIONS: LP is a simple and reliable landmark for identification of the LA, potentially helping surgeons to prevent and manage intraoperative bleeding.

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 score0.031
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.046
GPT teacher head0.321
Teacher spread0.275 · 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

Citations11
Published2021
Admission routes1
Has abstractyes

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