Geographic distribution of babesiosis among dogs in the United States and association with dog bites: 150 cases (2000–2003)
Bibliographic record
Abstract
OBJECTIVE: To identify the geographic distribution of babesiosis among dogs in the United States and determine, for dogs other than American Pit Bull Terriers (APBTs), whether infection was associated with a recent dog bite. DESIGN: Retrospective study. ANIMALS: 150 dogs. PROCEDURE: Canine blood samples submitted to the North Carolina State University Vector-Borne Disease Diagnostic Laboratory between May 2000 and October 2003 for which results of a Babesia-specific polymerase chain reaction assay were positive were identified, and breed and geographic origin of dogs from which samples were obtained were recorded. History and hematologic abnormalities for dogs that were not APBTs were recorded, and possible associations with a recent dog bite were examined. RESULTS: Dogs positive for Babesia DNA were located in 29 states and 1 Canadian province (Ontario). Babesia gibsoni was the most commonly detected species, with B gibsoni DNA detected in blood samples from 131 of 144 (91%) dogs. Of the 131 dogs positive for B gibsoni DNA, 122 (93%) were APBTs. Of the 10 dogs positive for Babesia canis vogeli DNA, 6 were Greyhounds. In dogs other than APBTs, there was an association between having recently been bitten by another dog, particularly an APBT, and infection with B gibsoni. CONCLUSIONS AND CLINICAL RELEVANCE: Results document an expansion of the known geographic range for babesiosis among dogs in the United States. Testing for babesiosis should be pursued in dogs with clinicopathologic abnormalities consistent with immune-mediated hemolytic anemia or thrombocytopenia, particularly if there is a history of a recent dog bite.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".