Bibliographic record
Abstract
Stone extraction devices are an important part of ureteroscopic stone extraction and laser lithotripsy. The instruments have evolved significantly as more advanced and miniaturized flexible ureteroscopes have been developed. Currently, tipless nitinol stone baskets are available from a number of manufacturers. The nitinol baskets do not affect the deflection of the flexible ureteroscope and can also be used with semirigid ureteroscopes. There is a reduction in the flow of irrigant with the use of stone extraction devices, but this is proportional to the size of the device. Nitinol baskets are safe for use in all parts of the collecting system and should be considered a standard first choice when a stone basket is used. Dormia helical and Segura flatwire baskets remain available commercially and may be useful in select cases but are not commonly used.Antiretropulsion devices, as well as BackStop (Cook Urological, Bloomington, IN, USA) and basket retention of a stone during laser lithotripsy, can reduce the migration of ureteral stones to the kidney during ureteroscopic lithotripsy and help to avoid additional procedures. For the three devices available, some data is available showing safety, however further clinical studies are required to establish whether their routine use for ureteral stones is warranted and cost effective.The most feared complication of the use of stone extraction devices is ureteral avulsion. The use of these devices and stone extraction should only be performed under direct vision, while observing the urothelium slide over the stone. If basket impaction occurs, no further traction should be applied to the basket. Laser can be applied to the stone or the basket itself.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.041 |
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".