Training vs. racing: A comparison of arrhythmias and the repeatability of findings in Thoroughbred Chuckwagon racehorses
Bibliographic record
Abstract
Arrhythmias are commonly reported in exercising horses, however due to regulatory constraints electrocardiograms (ECGs) are acquired during training but not competition, raising questions about the repeatability of findings. The aims were (1) compare training and competition arrhythmias and (2) describe the repeatability of arrhythmias during maximal-intensity exercise. A convenience sample of 52 healthy Thoroughbreds (aged 8.7 ± 2.5 years) competing in the World Professional Chuckwagon Association were obtained, totaling 152 training or competition ECGs (2-7 ECGs/horse). Speed, heart rate (HR) and arrhythmias (supraventricular premature complex, SVPC; ventricular premature complex, VPC) were examined. Pre- and post-recovery (approximately 6 min) blood samples measured lactate and high-sensitivity troponin-T. Training and competition arrythmias were compared (Friedman's test) and reliability of repeated ECGs assessed (intraclass correlation; P < 0.05). Training vs. competition: Forty horses had clean tracing from training and competition (n = 80 ECGs); the number and type of arrhythmias were not different. In training, VPCs were present in 7/40 horses (median [interquartile range, IQR]/ECG; range; 0 [0,0]; 0-4) and 9/40 horses (0 [0,0]; 0-5) in active-recovery. In competition, VPCs were present in 7/40 horses (0 [0,0]; 0-8) and 8/40 horses (0 [0,0]; 0-5) in active-recovery. Arrhythmias were primarily single premature complexes. Training and competition speed, HR, lactate and troponin-T did not differ however, sampling was too early for peak serum Troponin-T levels. Repeatability: total arrhythmias between serial ECGs did not differ. The reliability to detect SVPCs and VPCs was poor to moderate, and poor, respectively. Overall, the total number of arrhythmias was repeatable, but the reliability of arrhythmia type was poor to moderate.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".