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Record W3158534189 · doi:10.7759/cureus.14671

Bilateral Facial Palsy: A Clinical Approach

2021· article· en· W3158534189 on OpenAlexaff
Alvin Yang, Vikram Dalal

Bibliographic record

VenueCureus · 2021
Typearticle
Languageen
FieldMedicine
TopicFacial Nerve Paralysis Treatment and Research
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicinePalsyEtiologyDifferential diagnosisPediatricsMedical diagnosisSarcoidosisPhysical examinationDiseaseMedical historyIntensive care medicineDermatologySurgeryPathology

Abstract

fetched live from OpenAlex

Bilateral facial palsy (BFP) is exceedingly rare, representing only 0.3%-2.0% of facial palsy cases. Unlike unilateral facial palsy, it is often caused by a serious underlying systemic disease and therefore warrants urgent medical intervention. The differential diagnosis is broad, and detailed history, physical examination, and investigations are essential for identifying the etiology. Common acquired causes in existing case series include Lyme disease, Guillain-Barré syndrome, sarcoidosis, trauma, and Bell's palsy. Palsy that develops rapidly is often caused by trauma, infections, or autoimmune disorders, whereas slow progressive palsy suggests neoplastic diseases. While management varies by etiology, the physician can consider early empiric corticosteroids given their efficacy in numerous differential diagnoses. Antivirals can be considered in those with a strong history of viral prodrome. In this paper, we present the case of a puerperal patient with BFP and discuss its differential diagnosis, diagnostic approach, and management.

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)0.002
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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.116
GPT teacher head0.424
Teacher spread0.308 · 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

Citations22
Published2021
Admission routes1
Has abstractyes

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