Prevalence of radiographic changes in yearling and 2‐year‐old Quarter Horses intended for cutting
Bibliographic record
Abstract
REASONS FOR PERFORMING STUDY: There have been many studies that document radiographic findings in young Thoroughbred and Standardbred horses. No such studies have been performed in Quarter Horses. OBJECTIVE: To describe the prevalence of radiographic changes in the stifles, tarsi, carpi and fetlocks of young Quarter Horses intended for cutting. METHODS: Radiographs of yearling and 2-year-old Quarter Horses were obtained from a radiograph repository and a private farm. The carpi, tarsi, fetlocks and stifles were evaluated and radiographic changes categorised by type and location. The frequency of changes was calculated and comparisons were made between the 2 age groups. RESULTS: Of 458 included horses, 408 (89.1%) had radiographic changes, most of which were in the tarsi (304, 69.4%) followed by the stifles (202, 44.5%), hind fetlocks (155 of 355, 43.7%), fore fetlocks (131 of 361, 36.3%) and carpi (27 of 342, 7.9%). Of the horses with stifle changes, 188 (93.1%) were in the medial femoral condyle (MFC). There was a significant difference between the age groups for changes on the distal intermediate ridge of the tibia (DIRT), hindlimb middle phalanx (P2) osteophytes and proximal tibial osteophytes. CONCLUSIONS: There is a high prevalence of radiographic changes in presale survey radiographs, especially in the stifles and tarsi, of young Quarter Horses intended for cutting. POTENTIAL RELEVANCE: Veterinarians examining presale radiographs at cutting horse sales should expect a high prevalence of radiographic changes in this population of horses. Work to determine the clinical relevance of these radiographic changes is currently ongoing.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".