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Percutaneous nephrolithotomy made easier: a practical guide, tips and tricks

2007· review· en· W2169107926 on OpenAlexaff
Raymond Ko, Frédéric Soucy, John D. Denstedt, Hassan Razvi

Bibliographic record

VenueBritish Journal of Urology · 2007
Typereview
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsPercutaneous nephrolithotomyFluoroscopyMedicinePercutaneousRenal stoneRadiologySurgeryInternal medicineUrinary system

Abstract

fetched live from OpenAlex

Percutaneous nephrolithotomy (PCNL) plays an integral role in managing large renal stones. Establishing percutaneous renal access is the most crucial step in the procedure and requires a thorough understanding of renal, retroperitoneal and thoracic anatomy to minimize the risk of complications. Moreover, access to fluoroscopy and the proper equipment are critical to ensuring complete stone removal. In this review we describe the technique of PCNL used in a high-volume endourology centre, where the urologist is involved in all aspects of the procedure.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.051
GPT teacher head0.379
Teacher spread0.328 · 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.

Study designOther design
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

Citations108
Published2007
Admission routes1
Has abstractyes

Explore more

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