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Record W4234138010 · doi:10.1017/cjn.2019.196

P.102 Expanded endoscopic endonasal approach for orbital apex decompression

2019· article· en· W4234138010 on OpenAlexvenueno aff
Kaiyun Yang, Yosef Ellenbogen, Almunder Algird, D Sommer, K Reddy

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2019
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Surgical Oncology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSurgeryDecompressionInverted papillomaOrbit (dynamics)Papilloma

Abstract

fetched live from OpenAlex

Background: The Endoscopic endonasal approach (EEA) has been gaining popularity in the past decade as an alternative to traditional transcranial and transorbital approaches. We have performed orbital apex decompression for a variety of pathological entities. Methods: We performed a retrospective chart review on patients who underwent EEA orbital apex decompression between January 1st 2010 and December 1st 2018 at McMaster University. Results: Eight patients underwent endoscopic endonasal orbital decompression at our center, including five male patients and three female patients. The mean age of our patients was 50.1 years. The different pathologies we treated included nasopharyngeal carcinoma, hemangioma, fibrous dysplasia, IgG4 disease, inverted papilloma, angioleiomyoma, and neuroendocrine paraganglioma. Five patients presented with visual symptoms. Postoperatively, one of these five patients improved to baseline, three had stable vision, another one had progressive visual decline despite surgical intervention. Conclusions: Endoscopic endonasal approach can be used as an alternative to decompress orbital apex pathologies in selected patients.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.044
GPT teacher head0.308
Teacher spread0.264 · 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 designCase report
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
Published2019
Admission routes1
Has abstractyes

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