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Record W2805085237 · doi:10.1139/cjas-2018-0019

Pen enrichment and sex interaction on growth performance and metabolite concentrations of autochthonous Windsnyer pigs kept in a high stocking density

2018· article· en· W2805085237 on OpenAlexvenueno aff
Mbusiseni Vusumuzi Mkwanazi, A.T. Kanengoni, M. Chimonyo

Bibliographic record

VenueCanadian Journal of Animal Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsAnimal scienceStockingBiologyMetaboliteBody weightBlood urea nitrogenAlkaline phosphataseEndocrinologyCreatinineBiochemistry

Abstract

fetched live from OpenAlex

The objective of the study was to determine the interaction of pen enrichment and sex on growth performance and blood metabolite concentrations of Windsnyer pigs. Forty-eight growing Windsnyer pigs of both sexes, with an average initial body weight of 21.6 (±9.01) kg were used. Daily feed intake and weekly body weights for each pen were measured. Blood was collected at the end of the experiment. Pen environment did not affect average daily feed intake (ADFI) and average daily gain. There was a pen environment and sex interaction on ADFI. Females in barren pens had higher ADFI than enriched females but ADFI in barren and enriched pens was similar for male pigs. Pigs in enriched environment were more efficient in converting feed into body weight than those in barren environment. There was an interaction of pen environment and sex on glucose, blood urea nitrogen (BUN), and alkaline phosphatase. Enriched males had higher albumin than males in barren environment. Enriched females had higher BUN than females in barren environment. It was concluded that enriched Windsnyer pigs housed at a density of 0.39 m2 per pig, particularly females, perform better than those in barren environments.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.020
GPT teacher head0.236
Teacher spread0.215 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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