An approach to canine behavioural genetics employing guide dogs for the blind
Bibliographic record
Abstract
The purpose of this study was to attempt to find related variables of the canine genome with behavioural traits of dogs maintained and tested in a guide dog facility which provided a relatively uniform environment. The study involved 81 Labrador Retrievers that were being trained as guide dogs. Each dog was taken on walk-out sessions in which the trainer weekly recorded observations that were related to behavioural traits. The records were subjected to key-word analysis of 14 behaviour-related words. A factor analysis on the appearance rate of the 14 key words or phrases resulted in the extraction of six factors that accounted for 67.4% of the variance. Factor 1, referred to as aggressiveness, was significantly related to the success or failure of the dog in qualifying as a guide dog, and was also related to the variable of litter identification. Factor 2, referred to as distraction, was related to the variable of trainer. Factor 3, activity level, was related to the variable of sex, and was significantly related to the polymorphisms of c.471T>C in the solute carrier family 1 (neuronal/epithelial high affinity glutamate transporter) member 2 gene and c.216G>A in the catechol-O-methyltransferase gene. The involvement of polymorphisms c.471T>C and c.216G>A in behavioural patterns related to activity level is similar to comparable genetic studies in other mammalian species. These results contribute to a greater understanding of the role of these genes in behaviour.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".