Dropped Gallstones Post Laparoscopic Cholecystectomy Mimicking Peritoneal Seeding: CT and Ultrasound Features
Bibliographic record
Abstract
PURPOSE: The purpose of this work was to investigate the ultrasound (US) and CT features of dropped gallstones mimicking peritoneal seeding in patients after laparoscopic cholecystectomy (LCC). METHOD: We describe the US and CT features of dropped gallstones mimicking peritoneal seeding in eight patients who underwent LCC. We also conducted a retrospective study of consecutive LCC patients who subsequently had CT to determine the prevalence of this condition. RESULTS AND CONCLUSION: The density of dropped gallstones on CT ranged from hypodense to partially or completely calcified nodules. Some stones did not have visible surrounding reaction, whereas others showed an enhancing halo. All stones were echogenic and demonstrated shadowing on US. The stones were located mostly on the right side of the abdomen, and the majority were around the liver. The prevalence of dropped gallstones post laparoscopic cholecystectomy was 4.2%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".