Date of birth and purchase price as foals or yearlings are associated with Thoroughbred flat race performance in the United Kingdom and Ireland
Bibliographic record
Abstract
Abstract Background Thoroughbred breeders aim to have foals born early in the season, but scientific evidence on the advantages for race performance is scarce and contradictory. Methods The association between date of birth and purchase price as foal/yearling, with race performance by the end of the second and third years of life of Thoroughbreds racing in flat races in the United Kingdom (UK) and Ireland (IRE) was assessed using negative binomial and zero‐inflated negative binomial models on the entire 2014–2015 UK/IRE foal crops ( n = 28,282). Results In total, 6666 and 9456 horses raced in UK/IRE flat racing by the end of their second and third years of life. Prize money and prize money per start decreased with each additional day beyond 1 January that the foal was born. Purchase price as foal and yearling was negatively associated with the number of races run, while it was positively associated with prize money and prize money per start by the end of the third year of life. Conclusions Foals born early in the season had higher earnings by the end of their second and third years of life than foals born later. Differences were more marked among males than females. The most expensive horses sold as foals or yearlings ran fewer races but earned more prize money and prize money per start than less expensive horses. Results from this population‐based analyses may inform strategies and management practices aiming to maximise horses’ racing performance potential and increase financial returns.
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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 | 0.002 | 0.001 |
| 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 | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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 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".