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Record W1999290912 · doi:10.1089/end.2006.0247

Is the Holmium:YAG Laser the Best Intracorporeal Lithotripter for the Ureter? A 3-year Retrospective Study

2007· article· en· W1999290912 on OpenAlexaff
Pawan Kumar Gupta

Bibliographic record

VenueJournal of Endourology · 2007
Typearticle
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsPan Am Clinic
Fundersnot available
KeywordsMedicineUreterRetrospective cohort studySurgeryHolmiumLaserOptics

Abstract

fetched live from OpenAlex

PURPOSE: To study the efficiency and safety of holmium:YAG laser lithotripsy for ureteral stones. PATIENTS AND METHODS: A series of 188 patients with 208 ureteral stones were treated with semirigid ureteroscopy and holmium:YAG laser lithotripsy from January 2003 to December 2005. Of the stones, 116 were lower ureteral, 37 middle ureteral, and 55 upper ureteral. RESULTS: The success rate was 92.7% at the time of ureteroscopy and 96.7% at 3 months. The failures were secondary to retropulsion of the stones (3.3%). There were no perforations and one stricture. Stenting was done in 90% of patients. CONCLUSIONS: The Holmium:YAG laser is an ideal intracorporeal lithotripter for ureteral calculi, with a high success rate and low morbidity.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.328
Teacher spread0.298 · 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

Citations77
Published2007
Admission routes1
Has abstractyes

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