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Record W2082799595 · doi:10.1002/lsm.20258

Urinary calculus fragmentation during Ho: YAG and Er:YAG lithotripsy

2005· article· en· W2082799595 on OpenAlexaff
Ho Lee, Hyun Wook Kang, Joel M.H. Teichman, Junghwan Oh, Ashley J. Welch

Bibliographic record

VenueLasers in Surgery and Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsEr:YAG laserLaserAblationLithotripsyLaser lithotripsyMaterials scienceLaser ablationImpact craterFluenceOpticsNuclear medicineMedicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: We tested Ho:YAG and Er:YAG laser ablation of human urinary calculi to determine if Er:YAG is a more efficient lithotripsy device. STUDY DESIGN/MATERIALS AND METHODS: Ablation efficiency of Ho:YAG and Er:YAG lasers was tested at varying energy settings, ranging from the damage threshold to clinical energy setting associated with Ho:YAG laser. Stones of known composition (calcium oxalate monohydrate (COM), cystine, and uric acid (UA)) were irradiated. Crater width, depth, and ablation volumes were determined using an optical coherence tomography (OCT). RESULTS: For all stones and energy settings, the Er:YAG laser produced deeper craters and larger ablation volumes than Ho:YAG laser. The Ho:YAG laser created wider craters during the multiple pulse process and the shape of craters was irregular. CONCLUSIONS: The Er:YAG laser is more efficient than the Ho:YAG laser for lithotripsy. The deeper craters produced by the Er:YAG laser is attributed to the high absorption of energy at its wavelength.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.026
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.290
Teacher spread0.272 · 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.

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

Citations52
Published2005
Admission routes1
Has abstractyes

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