Characterization of the genetic pool of the Canadienne dairy cattle breed
Bibliographic record
Abstract
BACKGROUND: Canadienne cattle are the oldest breed of dairy cattle in North America. The Canadienne breed originates from cattle that were brought to America by the mid-seventeenth century French settlers. The herd book was established in 1886 and the current breed characteristics include dark coat color, small size compared to the modern Holstein breed, and overall rusticity shaped by the harsh environmental conditions that were prevalent during the settlement of North America. The Canadienne breed is an invaluable genetic resource due to its high resilience, longevity and fertility. However, it is heavily threatened with a current herd limited to an estimated 1200 registered animals, of which less than 300 are fullblood. To date, no effort has been made to document the genetic pool of this heritage breed in order to preserve it. RESULTS: In this project, we used genomic data, which allow a precise description of the genetic makeup of a population, to provide valuable information on the genetic diversity of this heritage breed and suggest management options for its long-term viability. Using a panel that includes 640,000 single nucleotide polymorphisms (SNPs), we genotyped 190 animals grouped into six purity ranges. Unsupervised clustering analyses revealed three genetically distinct groups among those with the higher levels of purity. The observed heterozygosity was higher than expected even in the 100% purebreds. Comparison with Holstein genotypes showed significantly shorter runs of homozygosity for the Canadienne breed, which was unexpected due to the high inbreeding value calculated from pedigree data. CONCLUSIONS: Overall, our data indicate that the fullblood gene pool of the Canadienne breed is more diversified than expected and that bloodline management could promote breed sustainability. In its current state, the Canadienne is not a dead-end breed but remains highly vulnerable due to its small population size.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".