Detection of a large unnamed Babesia piroplasm originally identified in dogs in North Carolina in a dog with no history of travel to that state
Bibliographic record
Abstract
CASE DESCRIPTION: A 12-year-old 46-kg (101.2-lb) sexually intact male Labrador Retriever was evaluated because of lymphadenomegaly. The dog resided in Texas, and its travel history included many southeastern and eastern shore states but not North Carolina. CLINICAL FINDINGS: Following evaluation of the dog, a diagnosis of stage IVa intermediate- to large-cell lymphoma was made. A cyclophosphamide-hydroxydaunorubicin (doxorubicin)-vincristine-prednisone chemotherapy protocol was initiated. One week after the first chemotherapeutic treatment, a routine blood smear evaluation revealed single and paired intraerythrocytic large piroplasms that resembled Babesia canis. Via molecular testing, the organism was identified as a Babesia sp that had been detected previously in dogs in North Carolina. TREATMENT AND OUTCOME: The dog was administered imidocarb diproprionate (7 mg/kg [3.2 mg/lb], IM) on 2 occasions (3-week interval). At 1, 4, 15, and 50 weeks after the second treatment, blood samples were analyzed specifically for the North Carolina Babesia sp via PCR assay; the result of each assay was positive. CLINICAL RELEVANCE: Because of the morphologic similarity of the large piroplasm detected in dogs in North Carolina to B canis, molecular testing of large piroplasms detected in dogs is needed to definitively identify the infective Babesia sp. In the dog of this report, the infection was not eliminated following treatment with imidocarb diproprionate, which may have been a result of the immunocompromised state of the dog or the drug's ineffectiveness against this parasite. If imidocarb diproprionate is ineffective against the North Carolina Babesia sp, treated dogs may act as reservoirs of infection.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".