<i>In vitro</i> comparison of shock wave lithotripsy machines
Bibliographic record
Abstract
We tested the hypothesis that shock wave lithotripsy machines vary in the ability to fragment stones to small size. Calcium oxalate monohydrate, calcium phosphate, cystine and struvite calculi were fragmented in vitro with the Dornier HM3, Storz Modulith SLX, Siemens Lithostar C, Medstone STS-T, HealthTronics LithoTron 160, Dornier Doli S and Medispec Econolith lithotriptors. Stones were given 2000 shocks or the FDA limit. Post-lithotripsy fragment size was compared. Struvite calculi were completely fragmented by all devices. The mean incidence of calcium phosphate dihydrate, calcium oxalate monohydrate, and cystine stones rendered into fragments greater than 2 mm was 0% for the HM3, Modulith SLX and Lithostar C, 10% for the STS-T, 3% for the LithoTron 160, 29% for the Doli and 18% for the Econolith (p=0.04); 0% for the HM3, Modulith SLX, Lithostar C, STS-T and LithoTron 160, 4% for the Doli and 9% for the Econolith (p=0.15); 1% for the HM3, 0% for the Modulith SLX, 1% for the Lithostar C, 10% for the STS-T, 14% for the LithoTron 160, 3% for the Doli and 9% for the Econolith (p=0.44), respectively. Shock wave lithotriptors vary in fragmentation ability.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".