Pedigree analysis in the Arabian horse in Algeria: estimation of inbreeding coefficient
Bibliographic record
Abstract
The studbook of the Arabian horse used in this study is recognized by international authorities such as the WAHO (World Arabian Horse Organization). The pedigree file of the horses includes 1812 animals from 166 stallions (with an average of 10.11 ± 17.33 offspring) and 392 mares (with an average of 4.30 ± 3.76 offspring). The maximal pedigree depth was 18 generations. Inbreeding coefficients of horses present in our data were estimated using the software "Pedigree Viewer" and MTDFREML software on the basis of the provided pedigree. The estimation of the inbreeding coefficient for the 1812 horses showed that 1177 animals from all those present in the pedigree were consanguineous, with an inbreeding coefficients varying from 0,00002 to 0,265, with an overall mean of 0,0275 ± 0,001. The average value of the inbreeding coefficient in the population of Arabian horses in Algeria is thus relatively high. It is to be noticed that this average coefficient of inbreeding is less than the threshold established as problematic in the inbreeding literature (6%); however, 13.5% of the total population shows inbreeding coefficients above this threshold. It is therefore important to educate owners-breeders to the problems that consanguinity can generate, and to avoid as much as possible practices that increase inbreeding, such as a too intensive use of a major ancestor, the use of a too small number of breeding animals and the use of crosses between related individuals. All these measures are necessary to prevent rapid inbreeding increase, which would result in a significant loss of genetic diversity, with a medium-term potentially negative effect on racing performances and reproduction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".