Prevalence of Dal blood type and dog erythrocyte antigens (DEA) 1, 4, and 7 in canine blood donors in Italy and Spain
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to determine the prevalence of Dal, and DEA 1, 4, 7 blood types, in a population of canine blood donors from Italy and Spain. Three hundred and twenty blood donor dogs receiving an annual health evaluation were included in the study. DEA 1 blood type was determined using an immunochromatographic strip technique while Dal, DEA 4 and 7 blood types were determined with polyclonal antisera using agglutination on gel columns. RESULTS: Out of 320 dogs blood typed 7 (2 Cane Corso and 5 Doberman Pinschers) (2.2%) were Dal negative; 137 (42.8%) were positive for DEA 1; 320 (100%) were positive for DEA 4 and 43 (13.4%) were positive for DEA 7. CONCLUSION: This study showed a similar prevalence of DEA 1, 7 and 4 to that reported in previous studies in the same, and in different, geographic areas, and provides new data on the prevalence of the Dal blood group in Italy and Spain. There was no significant difference (P = 0.8409) between prevalence of Dal negative blood types found in our population (2.2%) and the prevalence reported in a canine blood donor population from the USA (2.5%). Our study identified Dal negative dogs in a previously tested breed i.e. Doberman Pinschers, but also the Cane Corso breed was found to have Dal negative dogs.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".