Neuroendocrine Tumor (Carcinoid) of the Appendix With Mucocele
Bibliographic record
Abstract
Acute right lower quadrant pain is a common emergency department presentation. Medical imaging has a main role to rule out appendicitis. Distinguishing between appendicitis and the other two major appendix pathologies, mucocele and carcinoid tumors, is not easy, but it is important for medical and surgical management planning. Appendix mobility is not usually assessed during sonography, but is it helpful? When comparing sonography and computerized tomography with histopathology findings to distinguish appendiceal pathologies, appendix mobility was found to be a key component. Appendix diameter, wall thickness, hyperemia, and surrounding echogenic fat are signs of an inflammatory process that will fix the appendix. Appendiceal carcinoids and mucoceles, on the other hand, will not initially have an inflammatory component for years, and thus patients present with only mild recurrent vague abdominal pain, normal blood work, and mild or borderline imaging findings. Sonography should be the first-choice medical imaging modality to rule out appendiceal pathologies because appendix mobility should be assessed and reported.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".