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Record W3172951220 · doi:10.1016/j.animal.2021.100261

Associations between behaviour and health outcomes in conventional and slow-growing breeds of broiler chicken

2021· article· en· W3172951220 on OpenAlexfundno aff
S.M. Abeyesinghe, Natalie Chancellor, D. Moore, Yu‐Mei Chang, Justine Pearce, T.G.M. Demmers, Christine J Nicol

Bibliographic record

Venueanimal · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
FundersRoyal College of Veterinary Surgeons Charitable TrustRoyal SocietyRoyal Society for the Prevention of Cruelty to AnimalsOpen Philanthropy ProjectUniversity of Guelph
KeywordsBroilerAnimal welfareBiologyBreedWelfareHUBzeroAnimal husbandryAnimal scienceFeather peckingVeterinary medicineFlockDemographyMedicineFeatherPet therapyEcology

Abstract

fetched live from OpenAlex

Broiler chickens are prone to a range of complex health and welfare issues. To support informed selection of welfare traits whilst minimising impact on production efficiency and to address a major gap in understanding, we systematically explored associations between health and behavioural indicators of broiler welfare. One conventional (CNV, n = 350) and two slow-growing broiler breeds (SGH and SGN, respectively n = 400) were reared from hatch in pens of 50 birds. Birds were assessed for health (gait, plumage cover and dirtiness, pododermatitis, hockburn, and leg deviations) at 2.2 kg liveweight according to the Royal Society for the Prevention of Cruelty to Animals Broiler Breed Welfare Assessment Protocol. Behaviour and resource-use of 10% of birds per pen, on days 29 (all breeds) and 43 (SGH and SGN), was (i) scan sampled every 60 min between three to six and between twelve to fifteen hours after photoperiod onset; and (ii) continuously sampled sequentially from focal birds for 3 min each in a random order, during 15 min observation periods at three and twelve hours after photoperiod onset. Binary logistic generalized linear models were used, to assess respective associations between pen prevalence of each health outcome and (i) pen mean percentage scans of behaviour, and (ii) pen mean frequency and duration per 3 min focal observation of behaviour. Better growth rate and feed conversion but poorer health outcomes (mortality, gait, pododermatitis, feather cover) were more prevalent in CNV. Strong associations between behaviour and several heath indicators revealed, (i) increases in side-lying inactive, sitting inactive, and use of the litter relative to other resources, as primary and general indicators of poorer health, and (ii) increases in standing inactive, perch use, walking, Comfort, High Energy and Exploratory behaviour as primary and general indicators of better health. Of these, changes in side-lying, standing inactive, walking, Comfort and High Energy behaviour were particularly sensitive to small differences in health outcomes important for breed acceptance in high-welfare schemes. Crucially these behavioural measures additionally represent motivational and affective aspects of welfare not captured by health measures and allow opportunity for earlier intervention. Thus, to provide a comprehensive assessment of broiler experience, behaviour should be incorporated into broiler welfare assessments.

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.051
GPT teacher head0.293
Teacher spread0.242 · 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".

Quick stats

Citations42
Published2021
Admission routes1
Has abstractyes

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