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Record W4317567445 · doi:10.1007/s00240-023-01406-w

Knowledge-map analysis of percutaneous nephrolithotomy (PNL) for urolithiasis

2023· review· en· W4317567445 on OpenAlexaboutno aff
Junhui Hou, Zongwei Lv, Yuan Wang, Xia Wang, Yibing Wang, Kefeng Wang

Bibliographic record

VenueUrolithiasis · 2023
Typereview
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsnot available
FundersShengjing HospitalChina Medical UniversityShenyang Science and Technology BureauNatural Science Foundation of Liaoning ProvinceNational Natural Science Foundation of China
KeywordsPercutaneous nephrolithotomyMedicineUreteroscopyNephrologyUrologyBibliometricsChinaPercutaneousInternal medicineGeneral surgeryLibrary scienceGeographyUreterComputer science

Abstract

fetched live from OpenAlex

Percutaneous nephrolithotomy (PNL) has been used in the treatment of urolithiasis for more than 20 years. However, bibliometric analysis of the global use of PNL for urolithiasis is rare. We retrieved the literatures on PNL and urolithiasis from Web of science core collection database. VOSviewer was used to analyze keywords, citations, publications, co-authorship, themes, and trend topics. A total of 3103 articles were analyzed, most of which were original ones. The most common keywords were "percutaneous nephrology" and "urolithiasis", both of which were closely related to "ureteroscopy". Journal of Urology and Zeng Guohua from the First Affiliated Hospital of Guangzhou Medical University were the most published journal and author in this field. The most productive country was the United States, and its closest partners were Canada, China, and Italy. The five hot topics were the specific application methods and means, risk factors of urolithiasis, the development of treatment technology of urolithiasis, the characteristics, composition, and properties of stones, and the evaluation of curative effect. This study aimed to provide a new perspective for PNL treatment of urolithiasis and provided valuable information for urologic researchers to understand their research hotspots, cooperative institutions, and research frontiers.

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), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.811
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.009
Bibliometrics0.0040.006
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.111
GPT teacher head0.418
Teacher spread0.308 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations9
Published2023
Admission routes1
Has abstractyes

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