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Record W2335933574 · doi:10.1139/cjas-2015-0054

Effect of continuous access to feeding stalls during mixing on behavior, welfare, and performance of group-housed gestating sows in different social ranks

2016· article· en· W2335933574 on OpenAlexvenueno aff
Lihua H. Wang, Yuzhi Z. Li

Bibliographic record

VenueCanadian Journal of Animal Science · 2016
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsnot available
FundersNational Pork Board
KeywordsWeaningAnimal scienceAggressionWelfareBiologyMathematicsPsychologySocial psychologyEconomics

Abstract

fetched live from OpenAlex

This study was conducted to evaluate a strategy of using feeding stalls to protect low-ranking sows in group-housing systems. Sows (n = 150, parity 1–9) were mixed at weaning in pens of 15 sows. Control pens allowed sows to access feeding stalls for 1 h of feeding daily during the initial 2 d after mixing. Treatment pens allowed sows to access feeding stalls continuously. Social rank was determined based on outcomes of aggressive interactions among sows after mixing. Low-ranking sows used the feeding stalls more frequently (P < 0.01) than high-ranking sows during the initial 6 h after mixing. Continuous stall access reduced frequency of aggressive interactions (P = 0.05) and, consequently, reduced skin lesions (P = 0.05) of sows in the pen. Neither continuous access to stalls nor social rank affected performance of sows. These results suggest that low-ranking sows used feeding stalls as hiding spaces to escape from aggressive interactions during mixing, which reduced skin lesions caused by aggression and improved the welfare of sows in the group-housing system studied.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.031
GPT teacher head0.314
Teacher spread0.283 · 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

Citations11
Published2016
Admission routes1
Has abstractyes

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