Association between TH/MAOB gene single nucleotide polymorphisms and excitability in Labrador Retrievers
Bibliographic record
Abstract
Excitability is a pivotal quality in guide dogs because moderately active dogs are more trainable. Excessive activity is associated with behavioral problems and pet surrender. Excitability is a highly heritable trait, yet the relevant genetic factors and markers associated with this condition are poorly characterized. In the present study, we selected six single nucleotide polymorphisms (SNPs) of two genes that are possibly related to excitability in dogs (TH c.264G > A, TH c.1208A > T, TH c.415C > G, TH c.168C > T, TH c.180C > T and MAOB c.199 T > C). We measured the excitability of dogs using seven variables from three behavioral tests: the play test (interest in play, grabbing in throw and tug-of-war), the chase test (following and forward grabbing) and the passive test (moving range and moving time). These behavioral tests are part of the Dog Mentality Assessment developed by Svartberg & Forkman. The activity scores in the guide dog group were higher than in the temperament withdrawal group, and significant differences were detected in the aggregate score (p = 0.02), passive activity score (p = 0.007) and moving range score (p = 0.04). Analysis using the Kruskal-Wallis test and non-parametric Steel-Dwass test to evaluate the relationship between these SNPs and behavioral variable scores revealed that TH c.264G > A was associated with aggregate scores of excitability-related behavioral variables (adj. p = 0.03), object-interaction activity scores (adj. p = 0.03), following scores (adj. p = 0.03) and forward grabbing scores (adj. p = 0.03) in Labrador dogs and MAOB c.199 T > C was associated with moving range scores in these dogs (adj. p = 0.004). However, these results had low power. To explain the behavioral traits, further genetic studies more reliable than candidate gene studies are needed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".