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Record W4385841186 · doi:10.46747/cfp.6908531

Approach to sialadenitis

2023· review· en· W4385841186 on OpenAlexaffvenue
Jonah Moore, Matthew T W Simpson, Natasha Cohen, Jason A. Beyea, Timothy Phillips

Bibliographic record

VenueCanadian Family Physician · 2023
Typereview
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsQueen's University
Fundersnot available
KeywordsSialadenitisMedicineReferralIntensive care medicineMEDLINEIncision and drainageAbscessSalivary glandDermatologyPathologySurgeryFamily medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To provide family physicians with a practical evidence-based approach to the management of patients with sialadenitis. SOURCES OF INFORMATION: MEDLINE and PubMed databases were searched for English-language research on sialadenitis and other salivary gland disorders, as well as for relevant review articles and guidelines published between 1981 and 2021. MAIN MESSAGE: refers to inflammation or infection of the salivary glands and is a condition that can be caused by a broad range of processes including infectious, obstructive, and autoimmune. History and physical examination play important roles in directing management, while imaging is often useful to establish a diagnosis. Red flags such as suspected abscess formation, signs of respiratory obstruction, facial paresis, and fixation of a mass to underlying tissue should prompt urgent referral to head and neck surgery or a visit to the emergency department. CONCLUSION: Family physicians can play an important role in the diagnosis and management of sialadenitis. Prompt recognition and treatment of the condition can prevent the development of complications.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.103
GPT teacher head0.322
Teacher spread0.219 · 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 designNot applicable
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

Citations17
Published2023
Admission routes2
Has abstractyes

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