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Record W2057275543 · doi:10.5489/cuaj.11036

Laparoscopic pyeloplasty: the standard of care for ureteropelvic junction obstruction

2011· article· en· W2057275543 on OpenAlexaffvenue
Anil Kapoor, Christopher B. Allard

Bibliographic record

VenueCanadian Urological Association Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicPediatric Urology and Nephrology Studies
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsUreteropelvic junctionMedicinePyeloplastyStandard of careGeneral surgerySurgeryHydronephrosisInternal medicineUrinary system

Abstract

fetched live from OpenAlex

Open pyeloplasty has been the gold standard treatment for ureteropelvic junction obstruction (UPJO). Endopyelotomy, in spite of its inferior effectiveness, was sometimes preferred in select patients owing to its less invasive nature. Fortunately, over the past 2 decades a superior minimally invasive treatment has emerged with success rates equivalent to open pyeloplasty and complication rates equivalent to endopyelotomy. It is for good reason that laparoscopic pyeloplasty has become the new standard of care for the treatment of UPJO. Ureteropelvic junction obstruction is marked by renal outflow obstruction and may be asymptomatic or result in pain and complications, such as renal failure, pyelonephritis and calculus formation. Surgical management of UPJO aims to provide symptomatic relief and preserve remaining renal function. Today, treatment usually consists of either laparoscopic pyeloplasty or endopyelotomy. Its effectiveness, versatility and safety make laparoscopic pyeloplasty the optimal treatment for UPJO in virtually all circumstances.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.017
GPT teacher head0.227
Teacher spread0.210 · 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 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

Citations11
Published2011
Admission routes2
Has abstractyes

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