Evaluation of the dynactin 1 gene in Leonbergers and Labrador Retrievers with laryngeal paralysis
Bibliographic record
Abstract
OBJECTIVE To sequence exons and splice consensus sites of the dynactin subunit 1 (DCTN1) gene in Leonbergers and Labrador Retrievers with clinical laryngeal paralysis. ANIMALS 5 unrelated Leonbergers with laryngeal paralysis, 2 clinically normal Leonbergers, 7 unrelated Labrador Retrievers with laryngeal paralysis, and 2 clinically normal Labrador Retrievers. PROCEDURES Primers were designed for the entire coding regions of the DCTN1 gene, a noncoding exon at the 5´ end of the gene, and a 900-bp single-nucleotide polymorphism (SNP)-rich region located 17 kb upstream of the DCTN1 gene by use of the CanFam3 assembly of the canine genome sequence. Sequences were generated and compared between clinically normal and affected dogs. The SNPs flanking the DCTN1 gene as well as a previously identified nonsynonymous SNP in exon 32 were genotyped in affected and clinically normal Leonbergers and Labrador Retrievers. RESULTS None of the affected dogs were homozygous for any mutation affecting coding regions or splicing consensus sequences. Of the 16 dogs tested for the missense SNP in exon 32, all were homozygous for the reference allele, except for 2 affected and 1 clinically normal Labrador Retriever and 1 clinically normal Leonberger. The DCTN1 gene sequences (5 dogs) and haplotypes of polymorphic markers surrounding the DCTN1 gene (all dogs) were not consistent with the hypothesis that laryngeal paralysis was associated with inheritance of the same DCTN1 disease-causing allele within all Labrador Retrievers or Leonbergers evaluated. CONCLUSIONS AND CLINICAL RELEVANCE Mutations in the DCTN1 gene did not appear to cause laryngeal paralysis in Leonbergers or Labrador Retrievers.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".