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Record W4389097500 · doi:10.24908/pocus.v8i2.16568

The Use of Point of Care Ultrasound in Diagnosis of Peritonsillar Abscess

2023· article· en· W4389097500 on OpenAlexvenueno aff
Brian Kohen, Melanie Perez, Jheanelle McKay, Rolando Zamora, Curtis Xu

Bibliographic record

VenuePOCUS Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicOtolaryngology and Infectious Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsPeritonsillar AbscessMedicineOtorhinolaryngologyEmergency departmentComputed tomographyAbscessRadiologyPoint of care ultrasoundUltrasoundSurgeryNursing

Abstract

fetched live from OpenAlex

The use of point of care ultrasound (POCUS) for diagnosis and treatment of peritonsillar abscess (PTA) is increasing 1. Proven advantages include improved diagnostic accuracy and treatment success rates as well as decreased otolaryngology consultation, computed tomography (CT) usage, return visits to the emergency department (ED), and length of stay 1. We present a case of a patient with a PTA that was diagnosed and successfully treated utilizing POCUS, avoiding the need for otolaryngology consultation and CT.

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)0.001
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 score0.015
Threshold uncertainty score0.151

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.027
GPT teacher head0.292
Teacher spread0.265 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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