Evaluation of the effectiveness of introducing new alleles into the gene pool of a rare dog breed: Polish Hound as the example
Bibliographic record
Abstract
The objective of the analysis was to check the possibility of enriching a gene pool of a rare dog breed by breeding use of dogs of unknown origin that are phenotypically similar to a given breed. The evaluation was performed using pedigree and mtDNA analyses applied to Polish Hounds. The results indicated the very limited breeding success of such dogs in relation to their contributions to the gene pool and to the number of their descendants used in breeding. Dogs of unknown origin accounted for 80.9% of the total number of breed founders while the proportions of their descendants used in breeding were equal to just 14.3 and 4.7% of the total number of dams and sires, respectively. Breeders are unwilling to use such dogs and kennel judges are critical of their quality and appearance which are inconsistent with the breed standard. This may be connected with their distinct breed affiliation detected by the mtDNA analysis which showed the presence of three mtDNA haplotypes in Polish Hounds differing by a large number of substitutions. The study leads to the pessimistic conclusions that chances of enriching gene pools through breeding use of dogs of unknown origin are rather slim. The case of the Polish Hounds shows that the success of programmes for improving the genetic condition of endangered dog breeds can only be achieved in coordination between breeders and kennel authorities, and with financing from the state.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".