Congenital stationary night blindness is associated with the leopard complex in the miniature horse
Bibliographic record
Abstract
OBJECTIVE: To determine if congenital stationary night blindness (CSNB) exists in the Miniature Horse in association with leopard complex spotting patterns (LP), and to investigate if CSNB in the Miniature Horse is associated with three single nucleotide polymorphisms (SNPs) in the region of TRPM1 that are highly associated with CSNB and LP in Appaloosas. ANIMALS STUDIED: Three groups of Miniature Horses were studied based on coat patterns suggestive of LP/LP (n=3), LP/lp (n=4), and lp/lp genotype (n=4). PROCEDURES: Horses were categorized based on phenotype as well as pedigree analysis as LP/LP, LP/lp, and lp/lp. Neurophthalmic examination, slit-lamp biomicroscopy, indirect ophthalmoscopy, and scotopic flash electroretinography were performed on all horses. Hair samples were processed for DNA analysis. Three SNPs identified and associated with LP and CSNB in the Appaloosa were investigated for association with LP and CSNB in these Miniature Horses. RESULTS: All horses in the LP/LP group were affected by CSNB, while none in the LP/lp or lp/lp groups were affected. All three SNPs were completely associated with LP genotype (χ(2) = 22, P << 0.0005) and CSNB status (χ(2) =11, P<0.0005). CONCLUSIONS: The Miniature Horse breed is affected by CSNB and it appears to be associated with LP as in the Appaloosa breed. The SNPs tested could be used as a DNA test for CSNB until the causative mutation is determined.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".