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Record W4391288382 · doi:10.4103/ua.ua_120_23

The Saudi urological association guidelines on urolithiasis

2024· article· en· W4391288382 on OpenAlexaff
Wissam Kamal, Raed A. Azhar, Saeed Bin Hamri, Abdulaziz H. Alathal, Abdulaziz Alamri, Tarek Alzahrani, Hussain Abeery, Yasser A. Noureldin, Mohammad Alomar, Abdulrahman Al Own, Mansour Alnazari, Majid Alharthi, Mohannad A. Awad, Abdulghafour Halawani, Hatem Hamed Althubiany, Abdulrahman F. Alruwaily, Philippe D. Violette

Bibliographic record

VenueUrology Annals · 2024
Typearticle
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsMcMaster UniversityNOSM University
Fundersnot available
KeywordsMedicineGuidelineTerminologyContext (archaeology)MEDLINEConsistency (knowledge bases)Health carePopulationQuality (philosophy)Evidence-based medicineFamily medicineAlternative medicineEnvironmental healthPathology

Abstract

fetched live from OpenAlex

Aims: The Saudi Urolithiasis Guidelines are a set of recommendations for diagnosing, evaluating, and treating urolithiasis in the Saudi population. These guidelines are based on the latest evidence and expert consensus to improve patient outcomes and optimize care delivery. They cover the various aspects of urolithiasis, including risk factors, diagnosis, medical and surgical treatments, and prevention strategies. By following these guidelines, health-care professionals can improve care quality for individuals with urolithiasis in Saudi Arabia. Panel: The Saudi Urolithiasis Guidelines Panel consists of urologists specialized in endourology with expertise in urolithiasis and consultation with a guideline methodologist. All panelists involved in this document have submitted statements disclosing any potential conflicts of interest. Methods: The Saudi Guidelines on Urolithiasis were developed by relying primarily on established international guidelines to adopt or adapt the most appropriate guidance for the Saudi context. When necessary, the panel modified the phrasing of recommendations from different sources to ensure consistency within the document. To address areas less well covered in existing guidelines, the panel conducted a directed literature search for high quality evidence published in English, including meta analyses, randomized controlled trials, and prospective nonrandomized comparative studies. The panel also searched for locally relevant studies containing information unique to the Saudi Arabian population. The recommendations are formulated with a direction and strength of recommendation based on GRADE terminology and interpretation while relying on existing summaries of evidence from the existing guidelines.

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)0.009
metaresearch head score (Gemma)0.044
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: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0120.008

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 head0.071
GPT teacher head0.380
Teacher spread0.309 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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