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Record W2344053521 · doi:10.3390/ani6050027

Basing Turkey Lighting Programs on Broiler Research: A Good Idea? A Comparison of 18 Daylength Effects on Broiler and Turkey Welfare

2016· article· en· W2344053521 on OpenAlexaff
K. Schwean-Lardner, Catherine J. Vermette, Marina L. Leis, H.L. Classen

Bibliographic record

VenueAnimals · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMelatoninBroilerCircadian rhythmWelfareBiologyDarknessphotoperiodismPecking orderNocturnalRhythmSleep deprivationAnimal scienceDemographyEndocrinologyEcologyInternal medicineEconomicsMedicineSociology

Abstract

fetched live from OpenAlex

Daylength used as a management tool has powerful implications on the welfare of both broilers and turkeys. Near-constant light results in many detrimental impacts, including lack of behavioural rhythms and circadian melatonin rhythms. Both are suggestive that sleep fragmentation could result in birds reared on long photoperiods, which can lead to the same negative health and physiological responses as total sleep deprivation. An indirect comparison of the welfare implications of graded levels of daylength on broilers and turkeys clearly indicate that long daylengths depress welfare by increasing mortality, reducing mobility, increasing ocular pathologies and changing behaviour in both species. Furthermore, long daylengths change melatonin secretion patterns and eliminate behavioural and melatonin circadian rhythms, which were measured in broilers in these works. However, feather pecking in turkeys was reduced when birds were exposed to long daylengths. Exactly how much darkness should be included in a management program to maximize welfare will depend on the species, the age of marketing, and in turkeys, bird gender.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.110
GPT teacher head0.341
Teacher spread0.230 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations24
Published2016
Admission routes1
Has abstractyes

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