Subdiagnostic Cushing's syndrome in a Labrador retriever diagnosed with progesterone‐secreting adrenocortical neoplasia and late liver metastasis
Bibliographic record
Abstract
Abstract A 5‐year‐old, neutered male Labrador retriever was presented for poor hair regrowth following clipping, lethargy, exercise intolerance, polyphagia, polydipsia, polyuria and heat‐seeking behaviour. A bradyarrhythmia due to a second‐degree atrioventricular block and poor cardiac contractility was found. On abdominal ultrasound, a left adrenal mass was detected, and a functional progesterone‐secreting tumour was diagnosed and confirmed on histopathology and electron microscopy. After the initiation of inodilator drug therapy and adrenalectomy with a subsequent decline in progesterone concentrations, the clinical signs resolved. The dog was represented 2 years later with similar clinical signs. The dog's progesterone concentrations were again elevated, and a metastatic liver mass was detected on abdominal ultrasound examination and computed tomography scan. After liver lobectomy, the diagnosis was confirmed on histopathology, the clinical signs resolved, and progesterone concentrations normalised. This report describes the presentation of a dog with progesterone‐secreting adrenocortical neoplasia and late metastasis.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".