Bibliographic record
Abstract
A case of acute appendicitis within an inguinal hernia known as Amyand’s hernia, is presented. Aymand’s hernia is a very rare condition. Amyand’s hernia is rarely diagnosed preoperatively. We report a very rare case of appendicitis presenting in an incarcerated inguinal hernia. It’s a first case report of Aymand’s hernia in laparoscopy. An 83-year-old woman was admitted to our emergency department with a painful groin mass. Ultrasonographic examination revealed a hernia sac containing suspected bowel segment. A diagnostic laparoscopy was performed initially and disclosed a inguinal hernia containing a strangulated appendix with a necrotic tip. Without inguinal incision, we were able to obtain a correct diagnosis and perform an appendectomy. This kind of hernia poses diagnostic and therapeutic dilemmas. Initial diagnostic laparoscopy is an invaluable adjunct in both diagnosis and treatment of incarcerated inguinal hernias. Aymand’s hernia is a rare condition in which the Ultrasound proves to be a most useful tool. Before the final choice of treatment, general surgeons should bear in mind this rare presentation of acute appendicitis. doi: http://dx.doi.org/10.4021/jcs194w
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".