Bibliographic record
Abstract
CONTEXT: The sellar region is the site of frequent pathology. The pituitary is affected by a large number of pathologic entities arising from the gland itself and from adjacent anatomical structures including brain, blood vessels, nerves, and meninges. The surgical pathology of this area requires the accurate characterization of primary adenohypophysial tumors, craniopharyngiomas, neurologic neoplasms, germ cell tumors, hematologic malignancies, and metastases as well as nonneoplastic lesions such as cysts, hyperplasias, and inflammatory disorders. OBJECTIVE: To provide a practical approach to the diagnosis of pituitary specimens. DATA SOURCES: Literature review and primary material from the University of Toronto. CONCLUSIONS: The initial examination requires routine hematoxylin-eosin to establish whether the lesion is a primary adenohypophysial proliferation or one of the many other types of pathology that occur in this area. The most common lesions resected surgically are pituitary adenomas. These are evaluated with a number of special stains and immunohistochemical markers that are now available to accurately classify these tumors. The complex subclassification of pituitary adenomas is now recognized to reflect specific clinical features and genetic alterations that predict targeted therapies for patients with pituitary disorders.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".