Population structure of a colony of dog guides
Bibliographic record
Abstract
The objective of this study was to describe changes in genetic diversity in a colony of dog guides since its founding. Two breeds, German Shepherds (GS) and Labrador Retrievers (LR), were evaluated. Data were pedigrees of 4,699 GS and 3,573 LR dogs bred for use as guides by The Seeing Eye, Inc., Morristown, NJ. Rapid increases in average pairwise numerator relationships occurred in both breeds, although the average was approximately one-third higher in the GS population than in the LR population. A similar trend was observed for average inbreeding. The rate of increase in inbreeding has slowed in recent generations. In the current generation, relationship and inbreeding for all animals averaged 25.3 and 26.2% in GS, and 15.5 and 22.0% in LR, respectively. Effective founder numbers initially decreased in GS until Generation 3, and then increased steadily. Effective founder number in LR constantly increased. There was a constant increase in effective founder number in LR. A similar pattern was noted for effective ancestor number as well. Founder genome equivalents were initially higher in GS but decreased over time in both breeds. Generation intervals averaged 23.7 mo in GS and 23.2 mo in LR. Sires had average service lives of 2.7 and 2.2 generations in GS and LR, respectively. Dams had average service lives of 2.1 generations in both breeds. Litter sizes averaged 5.1 and 7.4 pups per litter for GS and LR, respectively. Effective founder and ancestor numbers have slowly increased over time, and heterozygosity as measured by the number of founder genome equivalents in the population has increased. Limitations on the number of matings permitted for sires and service life of dams has led to a plateau for inbreeding and relationships. The importation of germplasm from other working dog colonies is desirable.
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 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 | 0.000 |
| 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".