Bibliographic record
Abstract
Acute mesenteric ischemia (AMI) is an uncommon yet highly lethal cause of acute abdomen in the emergency setting. Computed tomography (CT) imaging, in particular a biphasic protocol consisting of angiographic and venous phase scans, is widely used to corroborate non-specific clinical findings when suspicions of AMI are high. Techniques such as low kilovoltage peak scanning, dual energy acquisition, or a combined arterial/enteric phase can improve iodine conspicuity and evaluation of bowel enhancement. Biphasic CT with CT angiography is mandatory to directly assess for the 3 primary etiologies of AMI-arterial, venous, and non-occlusive mesenteric ischemia (NOMI), and the CT angiographic findings may be the first visible in the disease. In addition, numerous non-vascular CT findings have also been reported. Bowel wall thickening, mesenteric stranding, and ascites are common but non-specific findings that correlate poorly with disease severity. Pneumatosis intestinalis and portomesenteric venous gas, while not pathognomonic for ischemia, are highly specific in cases of high clinical suspicion. Bowel wall hypoenhancement is an early and specific sign but requires a protocol optimizing iodine conspicuity to confidently identify. Finally, intraperitoneal free air and solid organ infarcts are also highly specific ancillary findings in AMI. AMI occurs as a complication in 10% of small bowel obstruction (SBO) patients, and understanding imaging findings of ischemia in the context of SBO is necessary to aid in treatment planning and reduce over- and under-diagnosis of strangulation. Familiarity with the imaging features of ischemia by radiologists is vital to establish an early diagnosis before irreversible necrosis occurs.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.013 |
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".