Bibliographic record
Abstract
OBJECTIVE: To report the case of a 28-year-old woman who presented with hypercalcemia (total calcium =4.11 mmol/L), elevated parathyroid hormone (PTH) 24.6 pmol/L, normal parathyroid hormone-related peptide 7.8 pg/mL, and a 63 mm × 57 mm, poorly differentiated neuroendocrine carcinoma (small-cell type) pancreatic mass with liver metastases. INVESTIGATIONS AND TREATMENT: Hypercalcemia was acutely managed with intravenous fluids, pamidronate and calcitonin. Investigations for multiple endocrine neoplasia type 1 and parathyroid adenoma were initiated. The identified neuroendocrine tumor was treated with cisplatinum/etoposide chemotherapy. RESULTS: The pancreatic mass (56 mm × 49 mm) and metastases decreased in size with chemotherapy and calcium levels normalized. Eight months later, calcium increased to 3.23 mmol/L, PTH increased to 48.2 pmol/L, and the pancreatic mass increased in size to 67 mm × 58 mm. The patient was given a trial of cinacalcet but was unable to tolerate it. Chemotherapy was restarted and resulted in a decrease in the pancreatic mass (49 mm × 42 mm), a reduction in PTH levels (16.6 pmol/L), and calcium levels (2.34 mmol/L). CONCLUSION: Ectopic PTH secreting tumors should be considered when there is no parathyroid related cause for an elevated PTH. Recognizing the association between PTH and hypercalcemia of malignancy may lead to an earlier detection of an undiagnosed malignancy.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".