Bibliographic record
Abstract
Light emitted from a femtosecond laser is capable of plasma-induced ablation of various materials. We tested the feasibility of utilizing femtosecond-pulsed laser radiation (lambda=800 nm, 140 fs, 0.9 mJ/pulse) for ablation of urinary calculi. Ablation craters were observed in human calculi of greater than 90% calcium oxalate monohydrate (COM), cystine (CYST), or magnesium ammonium phosphate hexahydrate (MAPH). Largest crater volumes were achieved on CYST stones, among the most difficult stones to fragment using Holmium:YAG (Ho:YAG) lithotripsy. Diameter of debris was characterized using optical microscopy and found to be less than 20 microm, substantially smaller than that produced by long-pulsed Ho:YAG ablation. Stone retropulsion, monitored by a high-speed camera system with a spatial resolution of 15 microm, was negligible for stones with mass as small as 0.06 g. Peak shock wave pressures were less than 2 bars, measured by a polyvinylidene fluoride (PVDF) needle hydrophone. Ablation dynamics were visualized and characterized with pump-probe imaging and fast flash photography and correlated to shock wave pressures. Because femtosecond-pulsed laser ablates urinary calculi of soft and hard compositions, with micron-sized debris, negligible stone retropulsion, and small shock wave pressures, we conclude that the approach is a promising candidate technique for 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 | 0.001 | 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".