Spurious laboratory results associated with immunoglobulin M gammopathy in a dog with multiple myeloma
Bibliographic record
Abstract
An 11 year old female-neutered Labrador presented for facial swelling. Clinicopathological abnormalities included hyperglobulinemia, azotemia, hypercalcemia, nonregenerative anemia, thrombocytopenia, and spurious hypoglycemia. Normoglycemia was subsequently confirmed using a cage-side analyzer (AlphaTRAK, Zoetis, UK). Serum and urine protein electrophoresis documented monoclonal (immunoglobulin M) gammopathy with Bence-Jones proteinuria. Computed tomography imaging revealed a monostotic osteolytic bone-lesion, and bone marrow cytology and histopathology documented plasmacytosis with multiple myeloma oncogene 1 / interferon regulatory factor 4 positivity, consistent with multiple myeloma. Infectious disease testing initially indicated seropositivity for Leishmania, Borrelia, and Anaplasma spp.; however, Leishmania PCR (splenic and bone marrow aspirates), and paired serological titers for Borrelia and Anaplasma were negative. Consequently, initial serological results were considered to be false positive because of paraproteinemia-associated assay interference. Chemotherapy (prednisolone and melphalan combination therapy) was initiated, but the dog was euthanased 30 days later because of the development of pericardial effusion. This is a report of spurious serological (and other laboratory) results occurring secondary to monoclonal gammopathy in a dog.
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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 | 0.001 | 0.003 |
| 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) | 0.001 | 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".