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Record W7016006460

Welfare of horses transported to slaughter in Canada and Iceland: Assessment of welfare issues and associated risk factors

2014· article· en· W7016006460 on OpenAlexaboutno aff

Bibliographic record

VenueIslandScholar (University of Prince Edward Island) · 2014
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsnot available
Fundersnot available
KeywordsWelfareStunningAnimal welfareRisk assessment
DOInot available

Abstract

fetched live from OpenAlex

The welfare of horses transported for slaughter is a growing concern in several countries, including Canada, Iceland and the United States of America (USA). Slaughter of horses involves transportation of horses to a regulated facility and slaughter procedures such as lairage and stunning. The main objective of this study was to identify welfare issues and associated risk factors, particularly those associated with transportation.\nA welfare assessment protocol was developed to identify pertinent welfare issues, such as injuries, dehydration and fitness for transportation. Prevalence of horses with injuries, a pre-existing clinical condition, a body condition score of less than 3 (on a scale of 5) and those in a non-ambulatory state were calculated. Skin temperature, respiration rate, blood lactate concentration, blood glucose concentration, plasma osmolality, plasma total protein concentration and packed cell volume were also measured.\nWelfare assessment of horses in Iceland was undertaken before and after transportation to the slaughter plant and at slaughter. Forty six journeys lasting up to 3 hours were studied. Welfare issues identified were the prevalence of bruising and dehydration. Adults were more prone to bruising and dehydration than foals. Some horses showed signs of consciousness after stunning (1.6%) indicating ineffective stunning.\nIn Canada, a prospective study observed 150 truckloads of horses after transportation to a Canadian slaughter plant. Associations between risk factors and welfare outcomes were evaluated using linear regression models. Welfare issues identified were prevalence of injuries, pre-existing clinical conditions, low body condition scores, and the presence of some non-ambulatory horses. There was a significant association between journey duration and the number of horses per truckload with injuries. Signs of dehydration were identified and were associated with journey duration and season. Blood lactate concentration at slaughter indicated increased anaerobic metabolic activity, which was affected by season (summer or winter) and lairage duration.\nA retrospective study was performed by collating data from all shipper certificates obtained from USDA for journeys in 2009 from the USA to equine slaughter plants in Canada. This study identified journey durations range from one hour to 105 hours.\nSome injuries in horses transported for slaughter were visible at ante-mortem inspection, whereas other injuries, such as bruises were not visible until post-mortem examination. Digital infrared thermography (DT) was evaluated as a potential tool to detect bruising ante-mortem. A preliminary study to evaluate factors affecting skin temperature (as measured by DT) indicated that an outdoor environment significantly affected skin temperature measured on different regions of interest (ROI) compared with an indoor environment. However, thermal symmetry between ROIs was maintained in outdoor conditions. Using these findings, a second study was performed to evaluate the methodology to detect bruising ante-mortem. Sensitivity to detect bruising was low, possibly due to selection of horses that did not spend time in lairage (i.e. there was no equilibrium time for skin temperature to stabilise after transport).\nIn conclusion, in Canada, injuries and dehydration were mainly associated with journey duration, aggressive behaviour between horses and season. In Iceland, injuries and dehydration were mainly associated with age (adult or foal).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.278
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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