Monitoring return to cyclicity following removal of a granulosa cell tumor associated with precocious lactation in an 11-month-old Holstein heifer
Bibliographic record
Abstract
An 11-month-old Holstein heifer was presented to the Western College of Veterinary Medicine for evaluation of precocious lactation associated with a palpably enlarged right ovary. Ultrasound examination of the ovaries revealed a 6 inch (15 cm) diameter right ovary with a multilobulated appearance, and a small left ovary measuring 0.6 inches (1.6 cm) long by 0.3 inches (0.8 cm) wide. The mammary secretion was consistent with milk: fat-3.07%, protein-4.78%, and lactose-1.07% with a somatic cell count of 4.8?106/mL. Prior to removal of the right ovary by right flank laparotomy, serum hormone levels were measured: testosterone (0.01 ng/mL), estradiol-17? (9.1 pg/mL), progesterone (0.2 ng/mL), prolactin (5.8 ng/mL), luteinizing hormone (0.14 ng/mL) and follicle stimulating hormone (0.32 ng/mL). Gross examination revealed that the right ovary weighed 7.34 oz (208 g) and was composed of numerous cysts (0.2-1.6 inches [0.5-4 cm] in diameter) containing fluid or blood. Microscopically, foci of cells of a follicular or luteal nature were noted. The definitive diagnosis was a right ovarian granulosa cell tumor, and milk secretion declined rapidly following tumor removal. The left ovary was monitored ultrasonographically at weekly intervals to determine onset of cyclicity. Follicular activity resumed between three and four weeks post-surgery, followed by detection of a corpus luteum at day 32. The heifer became pregnant five months post-surgery, and has since delivered a live calf. This case represents only the second reported case of precocious lactation associated with a granulosa cell tumor, and suggests that cyclicity is likely to return to the contralateral ovary less than a month after tumor removal.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".