Relationship between dynamin 1 mutation status and characteristics of recurrent episodes of exercise-induced collapse in Labrador Retrievers
Bibliographic record
Abstract
OBJECTIVE: To identify characteristics of exercise-induced collapse in Labrador Retrievers and compare characteristics for dogs with various dynamin 1 gene (DNM1) mutation statuses. DESIGN: Retrospective cross-sectional study. ANIMALS: 109 Labrador Retrievers with a history of recurrent exercise-induced collapse, clinically normal behavior and gait between episodes, and no reason for collapse identified via medical evaluation. PROCEDURES: Data were collected via surveys from owners of dogs that were tested for an autosomal recessive DNM1 mutation causing DNM1-associated exercise-induced collapse (d-EIC). Dogs were identified as having d-EIC (homozygous for the mutation) or not having d-EIC (heterozygous for or without the mutation). Survey data were reviewed by an investigator unaware of the genotypes of dogs, and collapse characteristics were compared between groups. RESULTS: 74 dogs had d-EIC; 35 dogs did not have d-EIC. Dogs with d-EIC were young (median age, 12 months) at the time of the first collapse episode; collapse in such dogs typically originated in the hind limbs and was characterized by low muscle tone, clinically normal mentation, and rapid recovery. Dogs without d-EIC were older (median age, 23 months) than dogs with d-EIC; such dogs had various characteristics of collapse that were not consistent with a single disease. CONCLUSIONS AND CLINICAL RELEVANCE: Characteristics of exercised-induced collapse in Labrador Retrievers with various DNM1 genotypes were identified in this study; findings may help distinguish dogs with d-EIC from those with other types of collapse conditions. Characteristics of collapse in Labrador Retrievers that were not homozygous for the DNM1 mutation differed substantially among dogs and may have been attributable to multiple causes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".