Investigation of stone retropulsion as a function of Ho:YAG Laser pulse duration
Bibliographic record
Abstract
Stone retropulsion during Ho:YAG (λ = 2.12 μm) laser lithotripsy with various pulse durations (τp: 250 ~ 495 μsec) was investigated. Depending on pulse energy, optical pulse durations were divided into two regimes: short pulse (250~350 μsec) and long pulse (315~495 μsec). Retropulsion distance was measured as a function of pulse energy from 0.4 J to 1.2 J. Calculus phantoms made from plaster of Paris were ablated with a free running Ho:YAG laser using various optical fibers (200, 400, 600 μm) in water. In order to examine the ablation efficiency of two different pulse durations, a single pulse was applied, and the dynamics of the recoil action of a calculus phantom was monitored using a high-speed camera. The correlation among laser-induced topography, ablation volume, and retropulsion was evaluated. Higher pulse energy and larger fibers resulted in larger ablation volume and retropulsion. At a given pulse energy, optical pulses with different durations yielded comparable ablation volumes. The shorter duration pulses induced more retropulsion than longer pulses did at the same pulse energy. Larger retropulsion with the shorter pulse is thought to be induced by higher temperature at the vapor-solid interface, subsequently resulting in faster plume ejection with higher recoil momentum. The results suggest that a longer pulse could minimize retropulsion of the stone during lithotripsy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".