Analysis of current methods and Welfare concerns in the transport of 118 horses by commercial air cargo companies
Bibliographic record
Abstract
BACKGROUND: Studies on equine air transport practices and consequences are scarce. This prospective study aimed to describe horse and air journey details and practices, document how horse behavior and health changed during the air transport phases, quantify the occurrence of welfare issues, and identify possible associations between horse and journey details, air transport practices, and welfare issues. RESULTS: Data were collected from before departure to five days after arrival on 118/597 horses traveling on 32 commercial air journeys on different routes, varying in duration and conditions. Most horses were middle-aged warmblood females, 26% of which were pregnant, and being moved by air for sales. Before flying, most were quarantined (median: 18; IQR: 9-53 days), and their fitness for travel was certified by veterinarians. At the departure airports, external temperatures varied from - 6 °C to 33 °C, and horses were loaded by experienced flight grooms (median: 35; IQR: 15-40 years) into jet stalls (three-horse: 87%, two-horse: 13%). During the flights, horses were regularly watered (water intake median: 14 L) and fed ad libitum (feed consumption median: 8 kg). At the arrival airport, horses were unloaded from the jet stalls, and external temperatures ranged from - 5 °C to 32 °C. Then, all horses were transported to arrival quarantine by road. Air transport phases affected horses' health status and behavior; increased heart and respiratory rates and behaviors, such as pawing, head tossing, and vocalization, were mainly identified at departure and arrival. Horse interaction, nasal discharge, increased capillary refill time (CRT), and abnormal demeanor were observed more often one hour before landing while resting and normal capillary refill time were more often displayed five days after arrival (all P < 0.01). One hour before landing, horses with bad temperament and horses of unknown temperament were more likely to develop nasal discharge when transported in winter and autumn (P < 0.001). The likelihood of an increased CRT was associated with shorter flights in horses of unknown travel experience (P < 0.001). Ten horses were injured, and 11 developed pleuropneumonias (i.e., shipping fever). CONCLUSIONS: Air transport is a complex procedure with several different phases affecting horse health and behavior. Therefore, experienced staff should carefully manage each horse before, during, and after air journeys to minimize welfare hazards.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".