What is hiding in the hindgut sac? Looking beyond rectal carcinoma
Bibliographic record
Abstract
OBJECTIVES: Although rectal cancer is by far and large the most common pathology involving the rectum that needs imaging, there are many other important but less common pathological conditions affecting anorectal region. The objective of this pictorial review is to discuss the cross-sectional imaging features of less common anorectal and perirectal diseases. RESULTS: Although a specific histological diagnosis cannot usually be made due to considerable overlap in the imaging appearances of anorectal diseases, this review illustrates the cross-sectional imaging findings with emphasis on magnetic resonance imaging (MRI) that can help in narrowing down the differentials to a reasonable extent. TEACHING POINTS: • Variety of pathology exists in the anorectum apart from common rectal carcinoma • Anorectal diseases present as non-specific wall thickening indistinguishable from rectal carcinoma • Computed tomography (CT) and MRI can help in narrowing down the differentials, although often biopsy is warranted.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".