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Clinical Practice Guideline for Managing Acute Urinary Tract Infections in Adult Females in Saudi Arabia

2000· article· en· W2057899437 on OpenAlexaff
George Zajac, Maria Skeoch

Bibliographic record

VenueJournal for Healthcare Quality · 2000
Typearticle
Languageen
FieldMedicine
TopicUrinary Tract Infections Management
Canadian institutionsMcGill UniversityHEC Montréal
Fundersnot available
KeywordsGuidelineUrinary systemMedicineDipstickIntensive care medicineClinical PracticeFamily medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

The management of urinary tract infections at primary health clinics in Saudi Arabia varied widely and did not generally conform to modern recommendations. A clinical practice guideline was developed to standardize and modernize the approach in order to improve the quality of care and reduce costs. An algorithm was developed for the management of acute urinary tract infections in non-pregnant adult females. Guideline recommendations were generally well received, and acceptance was greater where users were involved in the initial stages of guideline development. The cost of managing urinary tract infections was reduced providing that reliance on dipstick analysis did not increase costs through increased misdiagnosis.

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)0.004
metaresearch head score (Gemma)0.011
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.141
GPT teacher head0.526
Teacher spread0.385 · 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
GenreMethods

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
Published2000
Admission routes1
Has abstractyes

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