<i>Babesia</i> nucleic acid prevalence among blood donors in southern Québec
Bibliographic record
Abstract
BACKGROUND: Tick-borne diseases are on the rise in Canada, and southern Québec is considered one of the highest-risk regions for Babesia emergence. Babesia is easily transmissible through blood transfusion and was the most common transfusion-transmitted infection in the United States before the implementation of nucleic acid testing (NAT) in 2020. Babesia NAT is not yet implemented in Canada, and prevalence studies are necessary for risk assessment. Therefore, Héma-Québec performed a new prevalence study in the summer of 2024. STUDY DESIGN AND METHODS: Whole blood and platelet donors were sampled between June 1, 2024, and October 31, 2024, in four high-risk administrative regions in southern Québec (i.e., Estrie, Montérégie, Montréal, and Mauricie-Centre-du-Québec). The samples were tested at the American Red Cross with a qualitative Babesia NAT, i.e., the Procleix Babesia assay. RESULTS: A total of 28,800 donations were collected and tested from four high-risk administrative regions of the province of Quebec. All donations tested negative for Babesia NAT. DISCUSSION: While public health data indicate that Babesia microti is emerging in southern Québec, to date, the risk of acquiring babesiosis through transfusion of blood products remains low. Partnership with public health authorities and clinicians remains essential to keep abreast of the emergence of such cases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".